Marine Spatial Data Infrastructures

Marine Spatial Data Infrastructures

By

TEEMU TARES

A Dissertation

submitted in partial fulfilment of the requirements for the degree of

MASTER OF SCIENCE

(Hydrographic Surveying)

Supervisor: Dr Claire Ellul

Course Director: Dr Jonathan Iliffe

6 September 2013

MARINE SPATIAL DATA INFRASTRUCTURES TEEMU TARES

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MSc Dissertation Submission

Student Name: TEEMU TARES

Programme: MSc HYDROGRAPHIC SURVEYING

Supervisor: DR CLAIRE ELLUL

Dissertation Title: MARINE SPATIAL DATA INFRASTRUCTURES

DECLARATION OF OWNERSHIP

I confirm that I have read and understood the guidelines on plagiarism, that I

understand the meaning of plagiarism and that I may be penalised for

submitting work that has been plagiarised.

I declare that all material presented in the accompanying work is entirely my

own work except where explicitly and individually indicated and that all sources

used in its preparation and all quotations are clearly cited.

I have submitted an electronic copy of the project report through turnitin.

Should this statement prove to be untrue, I recognise the right of the Board of

Examiners to recommend what action should be taken in line with UCL’s regulations.

Signature: Date 6 September 2013


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Abstract

Geographic information have been effectively used in terrestrial Geographic Information

Systems (GIS) for decades, but in relation to the sea and the seafloor, it is not easy partially

due to the three-dimensional and dynamic marine environment and, partially, because

operating and collecting spatial information is quite troublesome underwater in comparison

to the acquisition of, for example, satellite imagery over land.

Today, there are great efforts around the world to implement new systems to e.g. measure,

observe, monitor, manage and improve the marine environmental situation. It has become

evident that the status of the Global Ocean cannot be neglected and something must be

done differently in order to better protect the Ocean against environmental degradation

and harmful changes, which are mainly due to greedy over-exploitation of marine resources

and side-effects of over-population, when wastewaters are still led to the sea.

Marine Spatial Data Infrastructures are being implemented to bring marine information

more available to decision makers, organizations and people responsible for, or dealing

with, marine resources. The rational is that decisions concerning the Global Ocean (or, a

local sea) should be based on understanding instead of cravings.

In this dissertation, components of Marine Spatial Data Infrastructures were identified and

studied, and a simple prototype tested at the Department of Civil, Environmental &

Geomatics Engineering of University College London, UK. The study showed that there are

lots of open marine datasets, although their utilisation is not quite easy for a non-specialist.

This may change in the future thanks to Web Mapping tools being developed at the same

time, when spatial data are being more and more opened to the public.

The main result of this project was to bring together the principles, actors, policies,

technology, metadata, standards, services, data and geo-portals in relation to Marine Spatial

Data Infrastructures.

Keywords: Marine Spatial Data Infrastructure, MSDI, Spatial Data Infrastructure, SDI,

INSPIRE, GeoConnections, Digital Coast, Maritime Spatial Planning, MSP, Integrated Coastal

Zone Management, ICZM, Geographic Information System, GIS, Web Mapping Service, OGC,

Remote Sensing, GMES, Copernicus, GOOS, Marine Environment, Maritime Situational

Awareness, Marine Global Picture, Maritime Surveillance, Environmental Monitoring,

Hydrographic Surveying, Seafloor, Underwater, Sub-Sea, Sea, Ocean.


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Acknowledgements

I would like to thank my supervisor, Dr Claire Ellul for entrusting me this project. I had a

feeling that Marine Spatial Data Infrastructures will be a rather wide subject to study, but I

could not imagine how far-reaching, indeed. I am quite grateful for the encouragement and

advices of Dr Ellul at all stages of my work.

I am very grateful too to the director of our course, Dr Jonathan Iliffe, whose personal

teaching and guidance was invaluable during the MSc in Hydrographic Surveying course.

I would also like to extend my appreciation to the University College London members of

staff at CEGE, and, specifically, to Liz Jones, Dr Paul Groves, Prof Marek Ziebart, Prof Richard

Simons and Dietmar Backes.

Last, but not the least, I thank my family for their limitless support and trust in my efforts.


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Abbreviations

3D Three-dimensional

API Application Programming Interface

AODC Australian Ocean Data Centre

ASCII American Standard Code for Information Interchange

BODC British Oceanographic Data Centre

CEGE UCL Department of Civil, Environmental & Geomatic Engineering

CBA Cost-Benefit Analysis

CF Climate and Forecast metadata convention

Copernicus Global Monitoring for Environment and Security (GMES)

CORBA Common Object Request Broker Architecture

CMSP Coastal and Marine Spatial Planning

CSDGM FGDC Content Standard for Digital Geospatial Metadata

CSV Comma Separated Value

CSW OGC Catalogue Service for the Web

DBMS Database Management System

DEM Digital Elevation Model

EEA European Environment Agency

EO Earth Observation

EU European Union

FAO Food and Agriculture Organization of the United Nations

FGDC Federal Geographic Data Committee

FOSS Free Open Source Software

FTP File Transfer Protocol

GEBCO General Bathymetric Chart of the Oceans

GeoREL Rights expression language for geographic information


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GESAMP Scientific Aspects of Marine Environmental Protection

GI Geographic Information

GIS Geographic Information System

GISCO Geographical Information System at the European Commission

GMES Global Monitoring for Environment and Security (Copernicus)

GML OGC Geography Markup Language

GOOS Global Ocean Observing System

GSDI Global Spatial Data Infrastructure

HDF Hierarchical Data Format

HO Hydrographical Office

HTML Hypertext Markup Language

ICZM Integrated Coastal-Zone Management

IEC International Electrotechnical Commission

IHO International Hydrographic Organization

IMO International Maritime Organization

IMP Integrated Maritime Policy

IPSO International Programme on the State of the Ocean

ISO International Standardization Organization

INSPIRE Infrastructure for Spatial Information in Europe

KML Keyhole Markup Language

LADM Land Administration Domain Model

LAT Lowest Astronomical Tide

LCML Land Cover Meta Language

MARPOL Intl Convention for the Prevention of Pollution from Ships

MOOS Monterey Ocean Observing System

MSDI Marine Spatial Data Infrastructure

MSP Maritime Spatial Planning


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NetCDF Network Common Data Format

NISO National Information Standards organization

NOAA National Oceanic and Atmospheric Administration

NSDI National Spatial Data Infrastructure

O&M Observation & Measurement

ODN Ordnance Datum Newline

OGC Open Geospatial Consortium

OLE Object Linking and Embedding

OS Operating System

PC Personal Computer

OS Ordnance Survey

PAR Photosynthetically Active Radiation

PI Place Identifier

RS Remote Sensing

SDI Spatial Data Infrastructure

SFS OGC Simple Feature Standard

SOAP Simple Object Access Protocol

SRID Spatial Reference System Identifier

SQL Structured Query Language

SVG Scalable Vector Graphics

SYKE Finnish Environment Institute

OBIS Ocean Biogeographic Information System

TCP/IP Transmission Control Protocol/Internet Protocol

UCL University College London

UI User Interface

UK United Kingdom

UML Universal Markup Language


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UN United Nations

UNCLOS United Nations Convention on the Law of the Sea

UNECE United Nations Economic Commission for Europe

UNEP United Nations Environment Programme

UNESCO United Nations Educational, Scientific and Cultural Organization

URL Uniform Resource Locator

UTM Universal Transverse Mercator

VROM Dutch Ministry of Housing

W3C World Wide Web Consortium

WCS OGC Web Coverage Service

WFS OGC Web Feature Service

WMC OGC Web Map Context

WMS OGC Web Map Service

WGS-84 World Geodetic System 1984

WSDL Web Services Description Language

X3D Extensible 3D

XML Extensible Markup Language

WWW World Wide Web


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List of Figures

Figure 1. Basic components of SDI (Souza and Delgado, 2012). ..................................................................... 6

Figure 2. The two concrete feet of the human society set to benefit of an SDI. .............................................. 7

Figure 3. Marine spatial data infrastructure themes (Fowler, Smith and Stein, 2011). .................................... 8

Figure 4. A generic MSDI architecture (after IHO, 2011). ............................................................................. 11

Figure 5. Fields of marine applications relying on the elements of SDI. ........................................................ 11

Figure 6. Utilization of spatial data by public sector in Finland (Mäkelä and Hilke, 2010). ............................ 13

Figure 7. Maritime service areas in the EU (GISCO, 2011). ........................................................................... 14

Figure 8. A possible SDI architecture (Steiniger, 2010). ............................................................................... 17

Figure 9. SDI software needs (Steiniger, 2010). ........................................................................................... 18

Figure 10. OBIS platform and architecture (Cleary and Fujioka, 2011). ........................................................ 19

Figure 11. Data inventory diagram of the Walloon Administration (MADAME, 2000). ................................. 21

Figure 12. The three types of ISO 19115 descriptors. .................................................................................. 22

Figure 13. Geospatial standardization (Nebert, 2013). ................................................................................ 23

Figure 14. Activities and standards in SDI (Nebert, 2013). ........................................................................... 24

Figure 15. INSPIRE Geo-portal (INSPIRE, 2013). ........................................................................................... 26

Figure 16. OGC Services (GSDI, 2009). ......................................................................................................... 29

Figure 17. Components of coastal and marine ecological classification (Arc Marine, 2013). ......................... 30

Figure 18. Block diagram of the UCL MSDI Prototype together with some remote services (e.g. Oracle). ..... 32

Figure 19. Connection to the UCL VPN. ....................................................................................................... 34

Figure 20. SSH tunnel has been opened to UCL GEGE. ................................................................................. 35

Figure 21. Test: QGIS Desktop GIS Client accessing and displaying data from the UCL GeoServer. ................ 36

Figure 22. Test: QGIS accessing and displaying swamps, rivers, lakes, depth contours etc. in Finland. .......... 37

Figure 23. Test: QGIS accessing and displaying a.o. bathymetry, satellite imagery and ports in Europe. ....... 38

Figure 24. Reverse pyramid effect (Bregt, 2012). ........................................................................................ 55

Figure 25. Cumulative costs and benefits of the NOAA Digital Coast service during a 5 years’ period. .......... 56

Figure 26. Open source SDI software (Steiniger, 2010). ............................................................................... 63

Figure 27. Freemind graphical approach to define a list of metadata elements (Neiswender, 2010). ............ 71

Figure 28. SFML data locator map (left) and download menu (right) (SFML, 2013). ...................................... 90

Figure 29. SeaDataNet user’s portal systems architecture (SeaDataNet, 2013). ........................................... 94

Figure 30. PRIMAR worldwide ENC coverage (on the left) in Finland (PIMAR, 2013).................................... 97

Figure 31. PRIMAR ENC search result from Nauvo (on the right), Finland (PIMAR, 2013). ............................. 97

Figure 32. PRIMAR worldwide ENC coverage around England (PIMAR, 2013). ............................................. 97

Figure 33. The most important waterways of Finland (Liikennevirasto, 2013). ............................................. 99

Figure 34. Pan-European marine metadata services (SeaDataNet, 2013). .................................................. 100

Figure 35. SeaDataNet direct access to data (SeaDataNet, 2013). .............................................................. 101

Figure 36. Arc Marine thematic layers (Wright et al., 2007). Cont. … ........................................................ 102

Figure 37. … Cont. Arc Marine thematic layers (Wright et al., 2007). ........................................................ 103

Figure 38. Ship track lines from 1980-2010 hydrographic surveys (GEBCO, 2011). ...................................... 104

Figure 39. Sea depth contours, lakes, rivers and swamps of South-East Finland highlighted. ...................... 105

Figure 40. CleanTOPO2 - 3D version rendered as an oblique view (Patterson, 2013). ................................. 106

Figure 41. Gravity from satellite altimetry, version 15, Sandwell & Smith, 2006. ....................................... 107


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List of Tables

Table 1. Coastal data model features/processes and geospatial data types (after Nyerges et al., 2007). ...... 10

Table 2. Spatial data themes mentioned in the INSPIRE directive, 14 March 2007. ...................................... 25

Table 3. A list of published ISO standards on geographic information. (See also page 74 etc.) ..................... 27

Table 4. Parts of the IHO S-100 standard (IHO, 2009). ................................................................................. 54

Table 5. INSPIRE annual requirements in million € as estimated in 2003. .................................................... 55

Table 6. Priority Commonwealth marine spatial information (Nairn, 2010). ................................................ 60

Table 7. Standards relevant to the OGC Hydrology Domain Working Group. ............................................... 76

Table 8. Topic categories of the Canadian GeoConnections Discovery Portal. .............................................. 91


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Contents

1 INTRODUCTION .................................................................................................................... 1

1.1 Motivation .................................................................................................................... 1

1.2 Objective ....................................................................................................................... 4

1.3 Outline .......................................................................................................................... 4

2 PRINCIPLES OF SDI ............................................................................................................... 5

3 SETTING UP A MARINE SDI .................................................................................................. 8

4 ACTORS ...............................................................................................................................12

4.1 Stakeholders, Users, Providers and Administrators ..................................................12

5 POLICIES AND ORGANISATIONAL STRATEGIES ..................................................................14

5.1 Cultural, Institutional, Policy and Legal Settings ........................................................15

6 TECHNOLOGY .....................................................................................................................17

7 METADATA .........................................................................................................................20

7.1 Purpose .......................................................................................................................21

7.2 Interoperability ...........................................................................................................22

8 STANDARDS ........................................................................................................................23

8.1 INSPIRE ........................................................................................................................25

8.2 International Organization for Standardization (ISO) ................................................27

9 SERVICES.............................................................................................................................28

10 DATA ...............................................................................................................................30

10.1 Core Datasets of Hydrographic Offices ......................................................................31

11 MSDI PROTOTYPE ...........................................................................................................32

11.1 Data Discovery ............................................................................................................32

11.2 Data Visualization .......................................................................................................33

11.3 Data Access .................................................................................................................33

11.4 Data Processing ..........................................................................................................34

11.5 Evaluation of the Prototype .......................................................................................34

12 DISCUSSION ....................................................................................................................39

12.1 Successes ....................................................................................................................39


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12.2 Shortfalls .....................................................................................................................39

13 CONCLUSIONS ................................................................................................................41

14 FURTHER WORK .............................................................................................................43

15 REFERENCES ...................................................................................................................44

16 APPENDICES ....................................................................................................................54

16.1 IHO S-100 Standard ....................................................................................................54

16.2 Cost-Benefit Analysis ..................................................................................................55

16.3 Actors (Cont.) ..............................................................................................................58

16.4 National SDI Monitoring and Assessment .................................................................61

16.5 Free Open Source GIS Software (FOSS GIS) ...............................................................63

16.6 Metadata (Cont.) ........................................................................................................69

16.7 Standards (Cont.) ........................................................................................................72

16.8 Services (Cont.) ...........................................................................................................80

16.9 Data (Cont.) .................................................................................................................82

16.10 Marine Geospatial Portals ......................................................................................89


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1 INTRODUCTION

1.1 Motivation The socio-economic value of marine areas of the world is huge. And, yet, as Dr James V.

Gardner, Research Professor of the Center for Coastal and Ocean Mapping tells: “We have

better maps of Mars. … We need to map the ocean, because it is totally unmapped. We

don’t know what’s there: Every time we map it, we find something new. It’s our Earth; it’s

where we live. It’s 70% of the surface of the Earth.” (GEBCO, 2011)

Meaden (2013) distinguishes 6 functions with especially broad socio-economic value:

1. Maritime trade and transport

2. Sea-food, nutrition, health and ecosystems services

3. Ocean energy and raw materials

4. Living, working and leisure in coastal regions and at sea

5. Coastal protection and nature development

6. Maritime monitoring and surveillance

Maximising short-term profits as opposed to sustaining exploitation in a long term is

revenging itself: “The whole global ecosystem is under enormous pressure mainly coming

from the increasing human population, which is attempting to extract resources at an

accelerating rate from a planet that is finite” (Meaden, 2013, page xxiv).

Conflicts are starting to emerge in those six functional areas listed above, calling for

Maritime Spatial Planning (MSP) or Coastal and Marine Spatial Planning (CMSP) in many

locations. “There is no doubt that GIS will be the technological basis on which marine spatial

management will best function” (Meaden, 2013, page 380). To be sustainable, marine

planning requires not only political, jurisdictional, socio-economical, technical etc.

information on paper, but people responsible for planning and exploitation must get to

know and understand the ocean, in particular.

The Agenda 21 resolution of the United Nations Conference on Environment and

Development in Rio de Janeiro in 1992 already addressed the need to stop and reverse

environmental deterioration. Spatial information is required for monitoring and making the

right decisions.

The International Programme on the State of the Ocean (IPSO) emphasizes that the Global

Ocean and the life within it are the least understood components on our planet. Subjected

to multiple human induced stressors from over-fishing and pollution, to acidification and

global warming, the Ocean is under the most unprecedented threat in human history, as

IPSO (2013) is pointing out with the following observations:


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Increased temperatures in the Ocean have been detected down to depths of 3000m.

Since 1978, summer sea-ice in the Arctic has decreased by over 7% per decade.

Carbon dioxide absorption has reduced pH levels in the Ocean, increasing its acidity.

75% of the global fish stocks are fully exploited, over-exploited or depleted.

Iconic marine species such as sharks and corals are disappearing from the Ocean.

Ocean ‘dead zones’ are spreading.

The SDI Cookbook (GSDI, 2009) also mentions increasing pollution, diminishing fish stocks,

toxic waste, crime management, business development, flood mitigation, land-use

assessment, disaster recovery and environmental restoration as examples, where Spatial

Data Infrastructures (SDI) are needed to support discovery, access, acquisition, use and

sharing of spatial information. To do it effectively, common conventions and technical

agreements towards interoperability between the local, regional, national and global Spatial

Data Infrastructures (SDIs) are required. Therefore, SDIs are being developed around the

world (GDI, 2009).

During the last 20 years, substantial progress towards interoperability of software and

datasets has indeed been achieved based on standards and data warehouses. Assimilating

spatial datasets in environmental, ecological, oceanographic, social, commercial, economic,

political, juridical and scientific frameworks is of great socio-economic benefit.

The benefits of a Spatial Data Infrastructure in a marine context enclose (IHO, 2011):

- Interoperability of datasets - Inter- and multi-organisational usage with increased efficiency - Reduced data duplication - Reuse of past datasets - More effective use of public funding - Division of costs - Improved ocean and coastal-zone management - Improved maritime spatial planning - Integrating marine and terrestrial data infrastructures and service providers - Cost savings through increased efficiency - Reduction of risk - Increased opportunities through availability of information - Wider user- and use-base for marine spatial information - Development of new products and services - Growth of new, non-navigational markets

Major application areas benefiting from marine geographic information, are related to

business and governmental mapping, analyses, maritime planning, national and

international development, law enforcement, health care, industry-related transportation,

route selection, vessel tracking, goods distribution, utilities services and management,


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military training, command, control and intelligence, natural resources inventory, harvest,

business planning, nature and cultural conservation, academic research and education, and

management of living species and environment (Meaden, 2013).

The real challenges confronted by maritime planners include (Seys et al., 2013):

- Increase in the volumes of remotely sensed and other data

- Diversity in data types: physicochemical, geological, meteorological and biological

- Discrepancy between the scales at which data are gathered and at which needed

- Global warming, sea-level rise, depletion of fish stocks, pollution etc.

- Integration of local datasets to support global decision-making

On the other hand, data and information can be exchanged in the internet quickly and at

very low cost, and improving computers and database systems make it possible to analyse

huge datasets and better manage the marine environment. Also international collaboration

and standardization are aiming at interoperable terrestrial and marine data infrastructures.

“While there are thousands of moored and free floating data buoys in the world's oceans,

thousands of land-based environmental stations, and over 50 environmental satellites

orbiting the globe, all providing millions of data sets, most of these technologies do not yet

talk to each other” (USGeo, 2012).

A Spatial Data Infrastructure (SDI) aims at supporting interoperable network discovery and

access to spatial data and services as well as metadata describing them, ancillary

information, software and hardware technologies, norms and standards, organisational,

national, regional and trans-national policies, laws, key actors, stakeholders, data providers

and users (Souza and Delgado, 2012).

Today, SDI appears to be beneficial both financially and environmentally that is motivating

its implementation.


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1.2 Objective A Spatial Data Infrastructure (SDI) brings together the people, legislation, data, services and

software and hardware systems to permit greater sharing of data within an organization,

regionally, nationally and internationally. Although this concept is relatively well established

in terrestrial GIS, it has perhaps only been recently identified as being relevant also to the

marine spatial framework.

Firstly, this project is to investigate marine-related SDI in relation to the following issues:

1. Scope and purpose for a Marine SDI - who will use it, where and how?

2. What kind of data is available mainly in the European focus?

3. What data standards exist that underpin interoperability for data sharing?

4. What software is available to host the data? Is there any data sharing software that

is already used in the Marine Environment? Is GIS software suitable for the marine?

5. What legislation helps or hinders data sharing in an international, marine context?

Secondly, in the end of this project, the focus is turned to attempt building a prototype

Marine SDI, reviewing and selecting software and marine data based on the earlier research.

1.3 Outline After the previous introduction to the item of Marine Spatial Data Infrastructures,

principles of Spatial Data Infrastructures (SDI) in general, will be described in Chapter 2.

Building on these Principles of SDI, basics of the Marine SDI will then be set up in Chapter 3.

Then, after Setting up a Marine SDI, Chapter 4 attempts to find out stakeholders, users,

providers, administrators, as well as their needs regarding to this setup.

Closely related to these Actors, there are Policies and Organisational Strategies, including

cultural and legal issues, which are studied in Chapter 5.

Chapter 6 is about Technology, having almost concurrent, but somewhat hidden role with

the living actors in today’s computerised world. The last five chapters are in fact an effort to

get deeper in the hardware and software issues, which are so crucial for the operation of

Marine Spatial Data Infrastructures. Therefore, the titles became: Metadata, Standards,

Services, Data and MSDI Prototype.

After the Discussion and Conclusions chapters, several Appendices have been enclosed.

This was done in order not to exceed the maximum length of the main part too much, while

keeping useful information intact.


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2 PRINCIPLES OF SDI In order to understand how a Marine Spatial Data Infrastructure should be constructed, and

the benefits to be derived from therein, it is first important to understand the fundamental

intent and components of a Spatial Data Infrastructure (SDI) and the stakeholders involved

in its creation and maintenance.

“The term Spatial Data Infrastructure was coined in 1993 by the U.S. National Research

Council to denote a framework of technologies, policies, and institutional arrangements that

together facilitate the creation, exchange, and use of geospatial data and related

information resources across an information-sharing community. Such a framework can be

implemented narrowly to enable the sharing of geospatial information within an

organization or more broadly for use at a national, regional, or global level. In all cases, an

SDI will provide an institutionally sanctioned, automated means for posting, discovering,

evaluating, and exchanging geospatial information by participating information producers

and users. SDI extends a GIS by ensuring geospatial data and standards are used to create

authoritative datasets and policies that support it” (Esri, 2010).

The Spatial Data Infrastructure (SDI) was defined by Kuhn (2005) by stating: “SDI is a

coordinated series of agreements on technology standards, institutional arrangements, and

policies that enable the discovery and use of geospatial information by users and for

purposes other than those it was created for.” The SDI Cookbook (GSDI, 2009), on the other

hand, defines SDI more compactly as “technologies, policies and institutional arrangements

that facilitate the availability of and access to spatial data.”

The objectives of Spatial Data Infrastructure are, following Steiniger (2010):

Distribution of spatial data

Standardization for interoperability

Providing central access point to data with cataloguing

Maintaining data by the original producer

Avoiding duplication of efforts

To spread the utilisation of spatial data, there must be a high-speed network that allows

data to be accessed easily and at low cost, shared effectively, the data itself must be

updated and be of assured quality produced by institutions being responsible for their tasks

(Souza and Delgado, 2012). This way the user can access any data from any source without

needing to worry about its interoperability.


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The basic five elements of SDI adapted from Souza and Delgado (2012), and Nebert (2013),

as presented in Figure 1, are:

1. Data and Metadata: Fundamental spatial datasets and information

o Maps, measurements, thematic, topological, topographical, statistical, names

2. Technology: Information technology and services

o Hardware, software, firmware, network, database, technical implementation

3. Regulation and standards: Technical agreements

o Data representation, transfer, utilization, interoperability

4. Policies and legislation: Institutional framework and arrangements

o Data sharing, security, privacy, governance, funding

5. Actors: Stakeholders, producers, providers, end-users, people and organisations

o Training, professional development, cooperation, outreach, actual utilisation

Figure 1. Basic components of SDI (Souza and Delgado, 2012).

The primary actors in SDI enclose possibly four levels:

1) engineers and scientists as data and service developers, 2) operational data producers and service providers, 3) coordinating bodies and organizations, and 4) scientists, engineers, decision makers, authorities, organisations and people as end-users.


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In a wider scope, an SDI may be seen not only as a network of information internal to the

human society, but as a system of feed-back between the nature and the human society,

where the society benefits of the SDI due to more efficient and sustainable use of natural

resources, as shown in Figure 2, where the human society is standing on two concrete ’feet’,

the Ecology and the Economy. And, if either collapses, so will the Society.

Figure 2. The two concrete feet of the human society set to benefit of an SDI.

It must be taken into consideration that, if SDI will be utilised mainly to increase the

exploration of natural resources - as it presumably will - SDI may not only fail to protect the

environment, but it will increase the rate of environmental deterioration through the

increased awareness and exploitation of natural resources.

Spatial Data (SD) are any data referenced to a specific location or geographical area, while

Spatial Services (SS) operate on these data. Services concentrate on discovering (i.e.,

searching, listing, finding), displaying, viewing (i.e., navigating, zooming, panning, overlaying

etc.), uploading, accessing, downloading, transforming (i.e., geocoding, ortho-rectification,

format transformation etc.) and processing (i.e., organising, classifying, calculating,

optimising, assimilating, producing maps etc.) spatial datasets as well as invoking other

interoperable services.

In principal, a Spatial Data Infrastructure (SDI) is based on spatial datasets and services, as

well as on their descriptions called Metadata, which is allowing data and services to be

found by non-native users and systems. In addition, SDI is based on the contributions of

end-users, developers, producers, added-value service providers and coordinating bodies.

Physically, an SDI requires different hardware and software components to work together

that will be introduced in two later chapters, namely Technology and MSDI Prototype,

starting on pages 17 and 32, correspondingly.

---

After these fundamentals of SDI, the next chapter will set up the Marine component of SDI.


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3 SETTING UP A MARINE SDI “Marine Spatial Data Infrastructure (MSDI) is the component of an SDI that encompasses

marine geographic and business information in its widest sense. This would typically include

seabed topography, geology, marine infrastructure, resources utilisation, administrative and

legal boundaries, areas of conservation, marine habitats and oceanography” (IHO, 2011).

MSDI places emphasis on the unlocking of hydrographic and all the other marine geospatial

information.

It has been estimated that only 10% of the sea floor has been surveyed to produce an

underwater digital elevation model (GEBCO, 2011) somewhat comparable to that available

globally on land. The Global Ocean covers about 72% of the surface of the Earth and holds

97% of the world’s water being an essential component of the Earth System. Moreover, very

little is known under the seafloor and in the deep sea. Therefore, the Ocean should be

investigated more thoroughly.

The need for a specific or integrated Marine Spatial Data Infrastructure comes back to the

United Nations Convention on the Law of the Sea (UN, 1983) under which marine

boundaries are required to be managed and made available by each country. Also Maritime

Spatial Planning (MSP), allocating rights for marine resources, defence, fisheries, monitoring

marine areas, intercepting illegal activities, quick maritime surveillance, legislation covering

oceans and ecosystem health, require detailed knowledge of maritime boundaries and

other marine information

Figure 3. Marine spatial data infrastructure themes (Fowler, Smith and Stein, 2011).

According to Cockburn, Nichols and Monahan (2004) cadastres have long been used on land

to register the boundaries of ownership and “cadastral surveying” and “legal surveying” are

often used interchangeably. Similarly to the land cadastre, a marine cadastre describes

spatial extents, rights, restrictions and responsibilities, as presented in Figure 3.


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Although the number of basic MSDI themes may currently be smaller than that of SDI, the

number will increase in the future, as MSDI is the main source of information for Maritime

Spatial Planning (MSP). Increasing environmental concerns and the largely unknown marine

environment will require new themes. For example, Integrated Coastal Zone Management

(ICZM) in the USA encompasses at least the following subjects.

- Site selection

- Coastal protection & shoreline management

- Emergency planning & management

- Licensing & consent evaluation

- Aggregates extraction & commercial exploitation

- Survey planning & execution

- Conservation of nature and human health

- Disposal monitoring

- Fisheries regulation

- Habitat mapping & heritage assessment

- Navigational charts, route optimization, vessel location monitoring

- Maritime security and safety of navigation

- Homeland security & defence

- Research, education and other applications of e.g. oceanography, hydrography,

geodesy, geophysics, geology, climatology, meteorology, biology and chemistry

Another example of MSDI themes is presented in Table 1 on the next page. An even more

detailed collection of thematic layers of the Arc Marine (2013) data model initiative is

presented in Figure 36 and Figure 37, respectively, on pages 102 and 103 in the Appendices.

Not only mariners are benefiting of MSDI while navigating, but there are several other even

greater benefits including safer and more effective shipping (that is transporting 90% of the

global trade), maritime spatial planning, coastal zone management, environmental

awareness, sustainable use and exploration of marine resources and national maritime

defence (IHO, 2011). Evidently, MSDI aims at providing data not only for producing

traditional nautical charts, but also for a wider audience with new application areas not yet

even discovered.

In the opinion of the writer, MSDI aims at bringing different geospatial data and services

together and using them to defend and gain the socio-economic values of marine areas of

the world, as already referred to in the very first sentence on page 1.

Societal and economic benefits of MSDI enclose improved Maritime Spatial Planning (MSP),

Ocean and Coastal Zone Management (OCZM), efficiency of maritime operations, maritime

safety, exploration and exploitation of marine resources, and maritime defence. Ecological

benefits of MSDI enclose environmental protection - as far as the negative effects of the

intensified commercial exploitation due to MSDI’s economic benefits don’t override it.


10

Table 1. Coastal data model features/processes and geospatial data types (after Nyerges et al., 2007).

Key

1. Step 1 features are compiled from ArcHydro and Arc Data Model info 2. Step 2 features are compiled from textbook information 3. Step 3 features are compiled from Near-shore Task Force info

Ultimately, an MSDI can support the action to “identify how humankind is changing the

capacity of the Global Ocean to support life and human societies on Earth” (IPSO, 2013).


11

A key principle of the European MSDI - as also in case of SDI - is to create data once and use

it multiple times, in order to limit data transfer and keep it up to date. This is illustrated in

Figure 4, where local Geoportals are accessing both a remote registry and database.

Figure 4. A generic MSDI architecture (after IHO, 2011).

Figure 5. Fields of marine applications relying on the elements of SDI.

Figure 5 is visualising the important elements of a Maritime SDI, which will be discussed

later. The next chapter will answer the question: Who will use MSDI and where?


12

4 ACTORS A working local, regional, national or global MSDI requires governance by the coordinating

public bodies and willingness for cooperation by the participating producers and providers

of data and services. End-users enclose mainly public organizations, but more datasets and

services are being developed and given free access to other organisations and people.

Hydrography forms the base spatial data layer for an MSDI in each state. In this framework,

the national Hydrographic Office (HO) possesses an unparalleled data and knowledge

resource according to the International Hydrographic Organization (IHO, 2010). In

cooperation with stakeholders the utilisation of hydrographic information can be advanced

to a new range and level of applications, enclosing improved decision making and data

management, increased organisational functions and market exposure efficiencies, more

effective use of public investments through cooperation and cost savings, among others.

IHO (2010) states that a HO should identify who are the other data providers, what data

they are providing, how is it complementing to that of the HO, who are the key persons to

get into contact with, what do they wish from the HO, how are they interacting with the

other involved SDI organisations, and what data sharing protocols they are supporting.

Moreover, according to IHO, it important to get to know SDI, how to develop and deliver it,

know the standards of data and metadata, have knowledge of the required Information and

Communications Technology (ICT) services, data base design and GIS software, and to do

team work in line with the SDI goals.

4.1 Stakeholders, Users, Providers and Administrators Public and private sector are in general the main sectors affected and focus is often on

environmental information. Marine spatial data infrastructure key stakeholders are related

to government, industry, coastal tourism, marine resources, transportation, science and the

general public. According to Nairn (2010) and GOOS (2013), they enclose:

- Environmental protection

- Coastal management

- Fisheries management

- Regional marine planning

- Hydrographic offices

- Oceanographic research

- National meteorological and oceanographic agencies

- Offshore oil, gas and minerals exploration and industry

- Other marine and coastal industries

- Transport and post security

- Maritime safety and security

- Parties to international conventions


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- Submarine cable and pipeline protection

- Indigenous interests

- Policy makers

User organizations involved in the “Users Requirement Definition” of MyOcean (2013):

- EMSA (European Maritime Safety Agency) as a MyOcean key user

- EEA (The European Environment Agency) as a MyOcean key user

- ECMWF (European Centre for Medium-Range Weather Forecasts) as a key user

- ICES (International Council for the Exploitation of the Sea) as a MyOcean key user

- FAO (Food and Agriculture Organization of the United Nations) as MyOcean key user

- HELCOM is working for the protection of the Baltic Sea against pollution.

- OSPAR has fifteen governments working for the protection of North-East Atlantic.

- UNEP/MAP (United Nations’ Environment Programme/Mediterranean Action Plan)

- National maritime safety, environmental and fishery agencies

- National Weather Services

- Climate Research centres

The public sector is the main end-user of geospatial information in Finland. And, according

to Mäkelä and Hilke (2010), the organisations in Figure 6 have had mutual GIS-related

businesses as shown by the connecting lines. The names are unfortunately in Finnish, but an

interested reader is advised to continue reading this subject on page 58, in the Appendices.

Similarly, “Customer Needs” analysis can be found on page 60, in the Appendices.

Figure 6. Utilization of spatial data by public sector in Finland (Mäkelä and Hilke, 2010).

Coastal and maritime activities have a huge socio-economic impact in Europe and

elsewhere, and, consequently, different policies and strategies for information sharing (or,

limiting it) exist. These policies are the subject of the next chapter.

http://www.emsa.europa.eu/

http://www.eea.europa.eu/

http://www.ecmwf.int/

http://www.ices.dk/indexfla.asp

http://www.fao.org/

http://www.helcom.fi/

http://www.ospar.org/

http://www.unepmap.org/


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5 POLICIES AND ORGANISATIONAL STRATEGIES Policy is related to strategic decisions on dissemination, access rights and distribution

control (Souza and Delgado, 2012) and it is linked to organization’s strategy for sharing

spatial information. For example, in EU the general MSDI policy is defined by the INSPIRE

Directive. In Canada, the corresponding policy is Geoconnections and in USA, Digital Coast.

“Marine SDI developments fit well with national, regional and world-wide initiatives aiming

at supporting environmental policies. Although SDI developments in general are led by land

mapping and cadastral agencies in most countries, the maritime dimension is increasingly

acknowledged as an important element, especially to implement integrated maritime

policies” (Ward, 2013).

The huge impact of coastal and maritime activities on the EU regions is clearly depicted in

Figure 7. It is shows the percentage of population living in areas, where maritime activities

have a socio-economic impact. This was calculated as the reachable areas within a given

time from coastal focal points (GISCO, 2011, page 24).

Figure 7. Maritime service areas in the EU (GISCO, 2011).


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5.1 Cultural, Institutional, Policy and Legal Settings Important legislation acts cover offshore settlements, seas and submerged lands, shipping,

marine pollution (MARPOL, International Convention for the Prevention of Pollution from

Ships), sea dumping, navigation, indigenous interests, maritime security like defence,

migration, customs and ports security, environmental protection and biodiversity

conservation, fisheries and other living marine resources, offshore minerals, cables and

pipes, and historic shipwrecks (Ward, 2013).

The London Convention (1975) and Protocol (2006) is one of the first conventions to protect

marine environment from human activities. Under the Protocol all dumping is now generally

prohibited, but dumping of the following items may be allowed after thorough impacts

analysis: Dredged material, sewage sludge, fish wastes, vessels and platforms, mining

wastes, organic material of natural origin, bulky items of iron, concrete etc., and carbon

dioxide streams from CCS processes (IMO, 2013). Also ocean fertilization research including

risk management and monitoring may be allowed.

EU legislation to protect the marine environment includes e.g. the Common Fisheries Policy

and the Water Framework Directive. These, however, are protecting the sea only from

specific fragmented pressures. That is why EU adopted two instruments, i.e. the EU

Recommendation on Integrated Coastal Zone Management and the EU Marine Strategy

Framework Directive as a more comprehensive protection of the European marine waters.

Further, the Integrated Maritime Policy (IMP) is the first time a policy has brought together

all the sectors that affect the oceans. The aim of the IMP is no less than to achieve the full

economic potential of the seas in harmony with the marine environment (EC, 2013).

Article 197 of UNCLOS (United Nations Convention on the Law of the Sea, originally adopted

in 1982) provides that states must cooperate for the protection and preservation of the

marine environment. IMO (International Maritime Organization) is cooperating in the

Regional Seas Programme of the United Nations Environment Programme (UNEP), having a

key role in the Scientific Aspects of Marine Environmental Protection programme (GESAMP)

and in combating marine pollution in general (IMO, 2012, page 81).

Articles 200 and 201 of UNCLOS provide for cooperation in promotion of studies, scientific

research programmes and exchange of information and data acquired about pollution of the

marine environment, and in the establishment of scientific criteria for the formulation and

elaboration of rules, standards and recommended practices and procedures for the

prevention, reduction and control of pollution of the marine environment. Articles 204 to

206 of UNCLOS contain provisions on the monitoring of the risks or effects of pollution and

assessment of the potential effects of planned activities under their jurisdiction or control

which may cause substantial pollution of or significant and harmful changes to the marine

environment. According to the article 261 and 262, the use of scientific equipment must not


16

constitute an obstacle to international shipping routes and such installations must bear

internationally agreed warning signals to ensure safety at sea, (IMO, 2012, page 82-85).

By contrast to the natural marine ecological boundaries, the jurisdictional maritime

boundaries either confirm to the exclusive economic zone of 200 nautical miles or to the

agreed boundaries between the neighbouring countries that leads to duality of marine

space division between the ecosystems and political jurisdiction. Without stronger

cooperation between the ecologically neighbouring countries, the ideal applications of MSDI

& GIS are unlikely to ensue (Meaden, 2013). Securing awareness of the importance of

marine spatial planning among higher levels of management or governance appears to have

received not much attention in the past, and, therefore, the underlying importance of

spatial association has not been appreciated enough at strategic planning levels.

At national level existing Information Technology (IT) legislation and policies need to be

reviewed, when establishing organizational data exchange policies also in order to address

privacy, intellectual property and security issues. Some national laws, licensing and

copyrights may be barriers, which cannot be overcome by geospatial SDI standardization.

For example, detailed hydrographic data may be considered as militarily sensitive

information, which therefore cannot be made neither freely nor commercially available.

Similarly, large energy companies and hydrographic surveying companies may tend to treat

“Big Data” acquired for their own purposes as a trade secret. These national or commercial

policies may be seriously hampering as well Maritime Spatial Planning and Integrated

Coastal Zone Management as protection of the unknown marine environment.

Obstacles to integration of marine policies include fragmentation, institutional structures,

divided legal competence, enforcement & compliance and complexity (Long, 2013).

---

The next chapter adds physical hardware and software to our scholarly study so far.


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6 TECHNOLOGY The SDI technology component includes hardware and software concepts such as web

services, ontologies, geo-portals, catalogues and framework of minimum set of data (Souza

and Delgado, 2012). Technology also includes hardware for data collection, ingesting,

processing, storage, GIS user interface and output, as well as devices and systems for data

transfer (Meaden, 2013). The technology enables the delivery of information for viewing,

transformation and downloading (IHO, 2011). This SDI hardware is shown in Figure 8.

Figure 8. A possible SDI architecture (Steiniger, 2010).

SDI’s basic software components are shown in Figure 9. And, according to Steiniger and

Hunter (2009) they consist of:

1. A software client to display, query, and analyze spatial data (browser or Desktop GIS)

2. A catalogue service for discovering, browsing, and querying the resources

3. A spatial data service allowing the delivery of the data via Internet

4. Processing services such as datum and projection transformations

5. Data repository for storing the data, e.g. in a Spatial database

6. A client or desktop GIS software to create and update spatial data.

Geospatial standards like WMS, WFS, GML, ISO 19115 (which are presented later), data

formats and internet transfer standards defined by the Open Geospatial Consortium (OGC),

International Standardization Organization (ISO) and W3C consortium, are necessary to

allow the interaction between the SDI software components to process vector and raster

data, make maps and transfer data.


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Figure 9. SDI software needs (Steiniger, 2010).

There are a limited number of large proprietary GIS software packages, which are used for

SDI and they may be suitable also for the Marine SDI. Compared to an SDI, similar type of

vector and raster data - but with different object names and properties - can be used in an

MSDI. The need for handling, visualisation and interpretation not only 2-dimensional, but

also 3D (depth) and 4D (dynamic), multi-dimensional, multi-sensor, multi-source, and,

especially, hyper-temporal data (and data formats such as netCDF), is probably the most

striking difference between SDI and MSDI. In the Global Ocean, there are lots of interrelated

phenomena that require of an MSDI the ability of dealing with very large volumes of data.

The Ocean Biogeographic Information System (OBIS), for example, was using PostgreSQL,

PostGIS, GeoServer, OpenLayers and Amazon Cloud Computing (Cleary and Fujioka, 2011).

This open source philosophy fits particularly well in the university research environment.

The OBIS architecture is graphically presented in Figure 10.

“It has been difficult to integrate spatial information from different systems and to integrate

spatial information into non-spatial information systems, because (McKee, 2003):

1. Different geo-processing systems, including vector/raster GIS, CAD, imaging,

transportation, navigation and management, produce very different types of data.

2. Different geo-processing systems produce data in different formats.

3. Different software libraries with interfaces restrict communication between systems.

4. Different data producers do not name spatial features in the same way.

5. Different data producers do not structure their metadata in a standard way.”


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Figure 10. OBIS platform and architecture (Cleary and Fujioka, 2011).

Other difficulties in MSDI are due to data being acquired by several kinds of instruments in

different types of surveys and stored in many different ways and data formats, informative

decision making requiring data assimilation not only from these sources, but also from other

sources such as chemical and biological observations. Moreover, metadata may be missing

or not conforming to the standards.

A most noteworthy commercial GIS software company in terms of market share is

Environmental Systems Research Institute (ESRI), whose major product is the ArcGIS

software package with several additional packages, such as Arc Marine and Arc Hydro.

“Performance is one of the key weaknesses of Arc Marine given its complexity and the

number of relationships and join operations needed to answer user requests” (Wright, 2013).

In case of the ocean visualisation, another commercial software i.e. Fledermaus, has

according to the knowledge of the author of this dissertation a long history of being a most

popular software for processing of sonar bathymetric and backscattering data. The new

Fledermaus-ArcGIS integration allows the data processed first in Fledermaus to be exported

to ArcGIS for final production of e.g. maps.

During the last few years there have appeared many quite promising Free Open Source

(FOSS) GIS packages, the most popular of them having large user base that is considered to

improve the quality as well as the functionality, because bugs are noticed and corrected

quickly and more and more new sub-routines implemented. The main advantage of FOSS

GIS is, of course, that it is free of charge and restrictions that was also the main criterion not

to consider any commercial software packages for this dissertation project. FOSS GIS

packages were therefore reviewed, the results of which are utilized in the MSDI Prototype

chapter on page 32. A more complete Free Open Source GIS Software review can be found

on page 63, in the Appendices.


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7 METADATA Metadata is officially used to describe the geospatial data and services in order to facilitate

searching and finding useful information. Metadata is useful to describe all type of data, i.e.,

not only emphasising the official data, but also anything else that can be useful to know in

the future for example telling about what was done in the project, what are the sources of

references and how good or bad something is (Nebert, 2013).

In EU, the cost of metadata is estimated to be about 20% of the INSPIRE SDI cost. For more

details, please refer to the Cost-Benefit Analysis on page 55.

The NISO guide (2004) states that "metadata is the key to ensure that resources will survive

and continue to be accessible into the future". Consequently, the marine spatial information

of today can in the long run potentially become part of the written human and natural

history, notwithstanding being partially in a machine-readable form. XML (Extensible

Markup Language) and GML (Geography Markup Language) are nowadays commonly used

for geographic data transactions over the internet.

Metadata can apply to data, services and other resource types by 1)providing inventory

documentation of existing internal spatial resources within an organization, 2)allowing

structured search of spatial resource catalogues by others and 3)providing end-users with

adequate information about how to utilize the resource correctly (Nebert, 2013). The

minimum set of SDI metadata should describe data type, extent, quality and the coordinate

reference system in order to facilitate discovery, retrieval and reuse, and to let users know

the basic characteristics for most efficient application (IHO, 2011).

The Geographic Reference System is an important part of the metadata, giving information

on both the horizontal and vertical datum and map projection used, for example: WGS-84

(World Geodetic System 1984) datum, ODN (Ordnance Datum Newline) or LAT (Lowest

Astronomical Tide) local or regional vertical datum, and UTM 30 (Universal Transverse

Mercator, zone 30) map projection. Iliffe and Lott (2008) are describing the datums and map

projections in detail in their book.

From a user perspective, however, everything else than the data and some application-

oriented services of interest may be considered more or less a nuisance especially, if a lot of

extra time and efforts are required in order to use the information. Metadata should

therefore be implemented in an automated process where ever feasible, to make its usage

invisible or at least as transparent as possible so that the human user’s experience will be

nice and work effective. The user needs the data to be certificate, official and of assured

quality that information is part of metadata, too.


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7.1 Purpose Metadata is very important, because otherwise there would be a great loss of time spent in

manually searching for existing datasets and services, investigating their usability for a

particular purpose and solving issues of incompatible data formats and services. Metadata

makes automation and interoperability of services possible, as described by Hogrefe and

Stocks (2010) by:

“Making data easier to manage without a need to repeatedly answer the same

questions about processing methods, quality etc.

Making data available to others through being able to find and use it.

Promoting readability of data-related information maintained in standard ways.

Fostering collaboration by raising awareness of quality and organizational activities.

Avoiding costly duplication of data or research, because information is easily found.”

Metadata is also used to describe spatial data and services in terms of access and use rights,

conformity with implementing rules, quality, validity, geographic location and responsible

public authorities, for example. A metadata service for managing spatial resources requires

choosing a right metadata standard, structuring the metadata databases for fast searching

and linking them to cartographic products, which are made available for a user through a

marine Web-mapping interface (MADAME, 2000).

Figure 11. Data inventory diagram of the Walloon Administration (MADAME, 2000).


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7.2 Interoperability The Institute of Electrical and Electronics Engineers (IEEE, 1990) defines interoperability as

the “ability of system components to exchange information and to use the information that

has been exchanged”. Metadata interoperability allows information systems to exchange

and use descriptive metadata about available data.

Neiswender and Montgomery (2009) emphasise as an important aspect that interoperable

metadata can be used by computer systems, in contrast to metadata that is designed to be

read by a person. Interoperable metadata allows, for example, tools such as address books

and drawing systems to easily import remote data, people to move spatial datasets

between various GIS systems, and a dataset to be found through multiple catalogues. To

ensure interoperability, metadata standards must be obeyed. Using standard vocabulary

helps in making metadata interoperable.

The ISO 19115/TS19139 standards provide the de facto standard for metadata and its

encoding (Nebert, 2013). The ISO TC 211 technical committee established the ISO 19115

standard for Geographic Information Metadata in 2003. ISO 19115 is facilitating the

interoperability of metadata services and is recommended to replace its predecessors.

There are eleven headings of which the following four are closely related to spatial

information (Barde et al., 2010): Reference system, spatial representation, content

information, and identification. Three ways of describing geographical extents are available:

(1) Toponyms, i.e. spatial keywords, (2) Cartographic objects with complex limits, and (3)

Cartographic box-like objects.

Figure 12. The three types of ISO 19115 descriptors.

Metadata searches are easier in the cartographic mode, where the user can do metadata

searches without needing to remember and type any text, which is thus recommended. For

ontological relationships developing multilingual thesauri (ISO 1985 for synonyms) can be

done using the ISO 5964 standard. Spatial relationships are based on OGC. In addition,

RDBMS like Oracle Spatial, MySQL Spatial (free) or Postgres/Postgis should be used.


23

8 STANDARDS “Standardization makes an SDI work. Standards touch every SDI activity. Standards include

specifications, formal standards, and documented practices” (Nebert, 2013).

In EU, the cost of Harmonisation of Data is estimated to be about 40% of the INSPIRE SDI

cost. For more details, please refer to the Cost-Benefit Analysis on page 55.

Examples of important international spatial standards enclose ISO 19100 series, IHO S-100

and the OGC standards. The main organizations related to standardization of terrestrial

geospatial information and services nationally or globally (GSDI), are shown in Figure 13.

Figure 13. Geospatial standardization (Nebert, 2013).

Well over 100 standards are relevant to SDI, for example in terms of interoperability, data

format, metadata, thesaurus and vocabulary. These activities are reflected in Figure 14.

Standards define technical data management in order to allow interoperability of data and

services. For example, it is important to use the ISO 19115 standard to ensure

interoperability between the MSDI, GIS, Remote Sensing (RS) and other processing systems.

The Open Geospatial Consortium’s (OGC) work on data content modelling, transport and

web services are critical to developing a robust SDI approach (IHO, 2011).

Framework data should be maintained for common goods and it consists of data layers for

transportation and utilities networks, hydrography, cadastral, administrative boundaries,

elevation, aerial etc. imagery and geodetic control points. ISO TC/211 metadata standard

and ISO/CD 19115 Geographic Information metadata standard provide methods for

describing these framework layers. ISO/CD 19107 Geographic information spatial schema

provides definitions for topology and geometry.


24

Figure 14. Activities and standards in SDI (Nebert, 2013).

Standards applicable to marine spatial data deal with metadata, Web-mapping, OpenGIS,

protocols, markup languages and sensor data standards, among others. A marine spatial

data repository should implement at least the following rules (Lassoued et al., 2009):

- ISO-19139 and Dublin Core metadata standards

- ISO-19115 core metadata set

- Quality information should be enclosed to metadata

- Catalogue Service for the Web to facilitate geospatial data discovery and access

- Geo-scientific ontologies should be implemented in the W3C standard languages

- Ontologies servers supporting the W3C query languages

- Web Feature Service (WFS) allowing geographical feature requests in the Web

- GML application based on data models like Arc Marine, Arc Geology and GeoSciML

- Web Coverage Service interface (WCS) standard for space/time varying phenomena

The ArcGIS Marine Data Model (Wright et al., 2007) is one of the more complex modelling

platforms for marine subjects, as depicted in in Figure 36 and Figure 37 on pages 102 and

103 in the Appendices. Arc Marine is targeted for the marine and coastal environment,

while e.g. GeoSciML is aimed at geological resources. Some data modelled with Arc Marine,

can be further interpreted in GeoSciML or Arc Geology that makes application of them all

useful.

“Just as data will be found through catalogues and registries, servers holding geo-

processing applications services will be discoverable anywhere among the WWW, through

service catalogues and registries” (Gould and Hecht, 2001).


25

8.1 INSPIRE INSPIRE is an EU initiative in order to develop a Spatial Data Infrastructure for Europe to

facilitate interoperable discovery and access to both local and global European levels. This

will be based on distributed databases with common standards. INSPIRE aims to set

common rules for this purpose. Services are needed for production and publication,

discovery, access and use. Also, understanding of geographic information is stressed.

“Making data available according to the INSPIRE standards in 30 countries using 22

languages requires specific skill sets that few public authorities have” (smeSpire, 2013).The

INSPIRE directive (2007) of the European Union defines 34 themes that a national Spatial

Data Infrastructure (SDI) must implement. The data themes are presented in Table 2.

Table 2. Spatial data themes mentioned in the INSPIRE directive, 14 March 2007.

The discovery and viewing services are available to the public free of charge (Official Journal,

1991, Article 14 in INSPIRE). Sharing of spatial data sets and services among public


26

authorities of the EU member states are enabled for tasks, which may have environmental

impacts. In addition, Community bodies of EU are provided with free data and services in

order to fulfil their obligations related to the environment.

“The INSPIRE Directive requires the Commission to establish a geo-portal (shown in Figure

15) and the Member States shall provide access to their infrastructures through the geo-

portal as well as through any access points they decide to operate” (INSPIRE, 2013).

The INSPIRE Directive (2007/2/EC) is targeted for solving environmental problems, directly

or indirectly. It states that “an infrastructure for spatial information in the European

Community should be established” in order to solve the availability, quality, organization,

accessibility and sharing problems related to many kinds of spatial information utilized

across the various levels of public authority. The Infrastructure for Spatial Information in the

European Community was established to assist policy-making that may have environmental

effects. The European Environment Agency and the European Environment Information and

Observation Network are actively contributing to the Inspire directive and providing reliable

environmental information for the EU (Official Journal, 1991).

Figure 15. INSPIRE Geo-portal (INSPIRE, 2013).


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8.2 International Organization for Standardization (ISO) ISO is the largest and most established developer and publisher of international standards.

It is composed of only national organizations. ISO/TC211 is the ISO technical committee

specialized in Geographic Information with standards specifying data, methods, tools, data

management, acquisition, processing, analysis, accessing, presenting, interoperable

applications, and transferring GI data between users, systems and locations (ISO, 2013).

ISO/TC211 is responsible for the 191XX series of standards for geographic information.

According to Nebert (2013), the standards highlighted below are especially relevant to SDI.

Table 3. A list of published ISO standards on geographic information. (See also page 74 etc.)

More information about standards is available starting on page 72, in the Appendices.


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9 SERVICES “Networks contain vast amounts of spatial information that are distributed among multiple

databases, stored in many formats and maintained by myriad of individuals and

organizations” (Kottman, 1999). Navigating these complex networks without services is

inefficient and confusing, when looking for information of interest.

In EU, the cost of Network Services is estimated to be about 30% of the INSPIRE SDI cost. For

more details, please refer to the Cost-Benefit Analysis on page 55.

Services are accessible through network interfaces allowing users to evoke behaviours using

standardized protocols. Three types of services are fundamental to SDI: data catalogue

services, on-line mapping services and access services. A broad range of other spatial

services exist. The OGC Service Framework, shown in Figure 16 identifies additional

processing and portrayal services, interfaces and exchange protocols that can be utilized by

any application and also form part of an SDI.

Many fundamental SDI services are related to data management and accessing data (GSDI,

2009) including: discovery and catalogue services, web-mapping, electronic commerce (e.g.,

http://www.commerce.net), authentication, payment confidentiality, public key

infrastructure, delivery and packaging, compression, sub-setting and sub-selection,

container-based delivery systems (e.g. http://www.paradata.com), data subscription, data

and file transport, HTTP, FTP, SMTP/MIME. Higher level services are related to data analysis,

usage and value-adding including: geo-processing, distributed computing, CORBA

(http://www.omg.org), COM, and a multitude of value-added spatial services related,

among others, to environmental, economical, industrial, social, juridical and political

applications and to specific sub-fields like meteorological research or fisheries policy taking

the advantage of spatial information.

The OGC Service Framework (GSDI, 2009) groups spatial services into five categories:

- Application Services, which are for human interaction with spatial information

- Catalogue Services, which are for the management of metadata

- Data Services, which are for the management of spatial data

- Portrayal Services, which are for human interaction with spatial information

- Processing Services, which are for processing of spatial information

A separation between spatial services listed above and IT services is made in ISO 19101.

And, there are six classes of IT services (GSDI, 2009):

- Human interaction services dealing with user interfaces, graphics, multimedia and

presentation of documents

- Model/information management services dealing with development, manipulation,

and storage of metadata, conceptual schemas and datasets

http://www.commerce.net/

http://www.paradata.com/

http://www.omg.org/


29

- Workflow/task services dealing with specific tasks conducted by humans

- Processing services dealing with computations involving spatial data

- Communication services dealing with data transfer in communications networks

- System management services dealing with management of systems, applications and

networks, including management of user accounts and access rights

- Standard service layers specified in INSPIRE include: CSW, WMS, WMTS, WFS, WPS,

WCTS and Atom

Figure 16. OGC Services (GSDI, 2009).

Important Services include: Atom Syndication Format (Atom), Web Authentication Service,

Catalogue Service (CSW), Web Coordinate Transformation Service (WCTS), NetCDF Climate

and Forecast (CF), Sensor Observation Service (SOS), Web Coverage Service (WCS), Web

Feature Service (WFS), Web Map Print Service (WMPS), Web Map Service (WMS), Web Map

Tile Service (WMTS), Web Perspective View Service (WPVS), Web Processing Service (WPS),

Web Security Service (WSS), Sensor Observation Service (SOS), Sensor Observation Service

(SOS), Symbolization (SLD), Routing Service, and Analysis and Topologic Overlay Service.

Please, view also the “Marine Metadata Standards” starting on page 72.


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10 DATA The most important MSDI component and of actual interest is the spatial information, i.e.

data, expressed in a consistent coordinate reference system. The two main data layers

enclose (1) the most commonly used spatial reference information and (2) application-

specific information, the latter of which may contain not only information on location, but is

e.g. business-related covering all the marine and maritime application areas.

The reference information enclose sub-layers like buildings, roads, railways, hydrography,

bathymetry, administrative boundaries, geodetic points, elevation, orthoimagery,

population, health, biology, chemistry, land cover, flood areas, economy or any other

spatially defined information. The latter may enclose specific surveillance & exploration

information, oil & gas, mineral extraction, renewable energy, fishing & mariculture,

construction & dredging & disposal, maritime infrastructure, submarine cables, pipelines,

marine recreation, tourism, conservation areas, species habitats, wrecks, coastal defence &

military activities, ports & maritime navigation, tides & currents, winds & waves, sea-ice,

(Green, 2010).

Biogeographic setting or eco-regions are defined by climate, geology and evolutionary

history. Aquatic setting is predominant in zones defined by salinity, coastal proximity and

tidal regime. Biotope is a combination of abiotic (i.e., inorganic) habitat and associated

species. This type of ecological classification is depicted in Figure 17.

Figure 17. Components of coastal and marine ecological classification (Arc Marine, 2013).


31

Ecological processes play a key role in Coastal and Marine Spatial Planning (CMSP), because

they are giving information on for example species diversity and distribution, setting a

foundation for processes happening in the ocean. Where the species are and how

productive they are is heavily influenced by oceanographic processes, which are very spatial

and dynamic. In addition to natural systems, of increasing importance are economic

services, which are giving CMSP information where specific actions are allowed and where

they should be prohibited. Another example is shipping, where the selected shipping routes

are a major use of the oceans having also important economic consequences for the

shipping companies. Political information about regulations and jurisdictional boundaries

are a guiding layer on what can happen and where that is a spatial component to feed in

this planning process. Social patterns (i.e., demographic information) where people are,

what type of people they are, what they are interested in getting from the ocean, how they

interact with each other, what is the social dynamics and social structure, and the network

of communities are all important factors on influencing what will come out of a particular

ocean region as we try to plan and manage it. All these and other spatial-related

information need to be fed in the planning process in the GIS platform (Halpern et al., 2012).

10.1 Core Datasets of Hydrographic Offices Most of the marine spatial datasets are owned or held by local or national hydrographic

offices (HOs). Types of core hydrographic data by theme include (IHO, 2010; NOAA, 2013):

Bathymetry including DEM (i.e., elevation), TIN, grid and points

Tidal information including water levels and tidal streams

Oceanography, e.g. sound velocity profile (SVP), salinity, temperature and currents

Navigational aids including buoys, lights and landmarks

Coastline, maritime borders, administrative limits and traffic separation schemes

Obstructions and wrecks

Hazards and climate

Ocean use

Seabed classification, benthic and land cover, e.g. rocks, sand and mud

Marine animals and habitat

Geographical names for seas, undersea features and charted coastal names

Maritime infrastructure: oil platforms, wind farms, pipelines and submarine cables

Shoreline infrastructure including jetties and tide gauges

Names of maritime spatial objects

To reduce data duplication and to guarantee that the updated data is of consistent quality,

it is important that the original data owner will be responsible for maintaining it.

Note! The reader should also view page 82 and 89, in the Appendices, as well as the

“Marine Metadata Standards”, starting on page 72.


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11 MSDI PROTOTYPE A Maritime SDI requires network services including metadata and data discovery, view,

access and transform. Due to simplicity, the MSDI compliance requirements on policy, law,

planning, data licensing, digital rights management, pricing and data processing were not

included in our MSDI prototype although they should be enclosed in a real MSDI. So, in

principal, the following 4 criteria for an MSDI prototype were tested: searching for metadata

(Discovery), data visualization (Viewing), download (Access) and use.

The Gulf of Finland was selected as the primary area of interest, but some of the datasets

covered the whole Baltic Sea or even the globe.

Figure 18. Block diagram of the UCL MSDI Prototype together with some remote services (e.g. Oracle).

The following chapters are explaining the configuration and a simple evaluation that was

performed by the author by using the UCL MSDI Prototype, shown above in Figure 18.

11.1 Data Discovery The 1st class of SDI Web services is the Discovery Service, which is typically provided by

national SDI catalogues, which can be accessed through related portals. Discovery requires

common metadata standards to be used to make the information about datasets

discoverable. Now, international standards (ISO 19115 and ISO 19139) exist for this purpose

and have been adopted by most countries. The first task is to make an inventory in general

on who has what data (physical variable) and where (location) of what type (raster, vector)


33

and quality (quality standard). SDI web services can then be utilized to discover the

metadata and incorporated information on data in detail.

11.2 Data Visualization The 2nd class of SDI services allows data to be presented interactively through services such

as WMS (Web Map Service) and WFS (Web Feature Service) using a standard interface over

the internet. Firstly, WMS is used to request and provide maps or their contents

information. Secondly, WFS is used to request and provide the data or search and access

spatial features.

11.3 Data Access The 3rd class of SDI Web services is needed to access raw geo-spatial data (not maps in case

of Web services) by downloading static data files through FTP or via Web Services using

common file formats such as NetCDF, HDF, GeoTIFF, XML and ASCII.

A single client can access multiple service targets. Examples of databases enclose MapServer

& PostgreSQL, Deegree & MS Access, ArcIMS & ArcSDE, Geomedia & AutoCAD, MapExtreme

& Oracle etc.), which are all accessed through the same standard OGC WMS Service layer.

WMS needs to be configured by setting an explicit service URL (Uniform Resource Locator)

defining the host, port and protocol used. In addition, the default data source, coordinate

SRID (Spatial Reference System Identifier), name of the mapping file, coordinate system

EPSG codes, list of layers to include, base map, and an explicit data source should be

specified. WFS service is used for publishing and editing data. All the WFS administration

steps are performed in SQL (Structured Query Language). Configuring the WFS enclose

setting server capabilities information, enabling database schemas, publishing tables as

feature types, register tables for updating, and notifying the WFS server (Godfrind, 2011).

In the opinion of the author, FOSS GIS (Free Open Source Software) is providing the general

interoperability required to be able to use an MSDI. Firstly, as a result of the FOSS GIS

review that is presented on page 63, in the Appendices, Quantum GIS (QGIS) appeared a

best candidate as a Desktop GIS Client not only due to its popularity. Secondly, GeoServer

was a good selection as a Web Map Server, because it is strong in standards, it is as good a

candidate as another strong FOSS server, MapServer, and last but not the least, it is already

in use at the University College London. Thirdly, deegree and GeoNetwork were also

available in UCL and connections were created and tested, as explained on the next page.

These two were not however utilised, because all the data could be well uploaded and

accessed at the UCL GeoServer.

In case of QGIS, the metadata is stored in the system project file and is not available to

other projects or other users of the same datasets. Another drawback in QGIS is that it is not

able to search metadata (Ellul, 2013a). This makes our MSDI prototype rather handicapped,

if connected to a larger data warehouse, although in our case the number of different

vector and raster files was so small (i.e., 17) that there was no need to search metadata.


34

Even in our case, however, it would have been important to be able to view detailed

descriptions of each database in order to use them correctly. Also, information on data

quality before and after the processing (Ellul et al., 2013b), as well as recorded processing

steps, would be an important addition to the metadata describing the dataset.

11.4 Data Processing The 4th class of SDI services allows spatial data to be processed by using Web Mapping

Service (WMS), Web Coordinate Transformation Service (WCTS), Symbolization (SLD),

Routing Service or Analysis and Topologic Overlay Service.

11.5 Evaluation of the Prototype Our MSDI prototype was based on the following techniques:

Virtual Private Network (VPN) connection protected by the student username and

password to the UCL Information Services Division (ISD) using the Cisco AnyConnect

Secure Mobility Client version 3.0.11042 installed in the local personal computer at

the author’s home, as shown in Figure 19. The purpose of a VPN is to secure the

internet connection by encrypting all data sent and received between the home and

UCL computers.

Figure 19. Connection to the UCL VPN.

SSH Secure Shell version 3.2.9 - also installed in the local PC - in order allow secure

network services by replacing other insecure terminal applications, such as Telnet,

FTP, X11 connections and arbitrary TCP/IP ports. As the remote installations of

iGeoPortal, GeoNetwork and GeoServer are behind a firewall in UCL, a secure

channel, i.e. a “tunnel” using SSH, needs to be created for the connection that, in our

case, is presented in Figure 20.


35

Figure 20. SSH tunnel has been opened to UCL GEGE.

Of the three applications mentioned above, a Free Open Source (FOSS) GeoServer

application was used, because in addition to being free, it allowed the required WCF,

WFS and WMS services.

Selected raster and vector data files, as explained below, were uploaded to a given

GeoServer folder.

Data was then accessed from the user’s desktop computer using Quantum GIS

(QGIS), which is one of the most popular and advanced FOSS GIS software available.

The uploaded Free and Open Source (FOS) data files included:

Colour-coded depth and relief shading of the ocean bottom, and, cross-blended

hypsometric data with relief, water areas, drainages and ocean bottom raster files

(Natural Earth, 2013), where the bathymetry is derived from the CleanTOPO2 data

(Patterson, 2013, shown in Figure 40), which is originally based on global seafloor

topography measured and estimated from gravity data from satellite altimetry in ca.

20km resolution and from much higher resolution, but unfortunately sparse

shipboard depth soundings derived by Smith and Sandwell (1997). Their original

dataset contains however artefacts, which are corrected in the CleanTOPO2 by

manual editing. It is useful to know that there is a better bathymetric dataset with a

3 kilometres resolution available (see: GEBCO, 2011), but due to some file format

conversion problems, the author of this dissertation could not make it readily

available. Note also that there exists an even much higher resolution (i.e. 45-60m)

dataset from the Shuttle Radar Topography Mission (Farr et al., 2007) measured

over the land surfaces. This digital elevation model (DEM) of all land between about

60° North latitude and 56° South does not reach the latitudes of Finland, however.


36

International shape files used include: 1:10,000,000 collection (Natural Earth, 2013)

of ports and populated places of the world, coastlines of the world, and bathymetric

contour lines for 0, 200, 1000, 2000 and 4000 meters.

National shape files used in 1:1,000,000 scale covering the whole country of Finland

are derived from the National Land Survey of Finland (Koordinates, 2013) containing

all the water-related areas, i.e., coastline, water depth, lakes, rivers and swamps.

QGIS (at author’s home in Finland) was connected to the GeoServer at UCL in London,

UK, and data was effortlessly accessed, as are shown by the next 3 figures below. The

first of them, i.e. Figure 21 shows administrative boundaries, coastline, islands, shaded

relief, water, drainages and bathymetric contours between 200 and 4000 meters.

Figure 21. Test: QGIS Desktop GIS Client accessing and displaying data from the UCL GeoServer.


37

Figure 22. Test: QGIS accessing and displaying swamps, rivers, lakes, depth contours etc. in Finland.

The Figure 39 on page 105, in the Appendices, presents a similar, but zoomed-in image over

southern Finland, where swamp areas, lakes, rivers and islands are well highlighted.


38

Figure 23. Test: QGIS accessing and displaying a.o. bathymetry, satellite imagery and ports in Europe.

This image shows the ports around Europe, in addition to bathymetry and satellite imagery.

All the data on the QGIS Layers menu, on the left above, are actually residing at UCL and

automatically transferred to QGIS through the Web Mapping Services, while the QGIS itself

is being run on author’s PC. I.e., no data is copied, but fetched from the UCL GeoServer.


39

12 DISCUSSION

12.1 Successes In the opinion of the author, GIS is a good tool for educating people and finding out gaps in

the knowledge of e.g. decision makers, if good MSDI data is available for the analysis.

Harmonisation of global datasets will be costly and difficult, if SDI standards are not obeyed.

If data originates from different sources, there will be compatibility issues and even errors,

but working always with the original data will reduce them. This is one of the most

important successes of MSDI, especially under INSPIRE and relatives.

According to cost-benefit analyses, the INSPIRE SDI appears financially quite beneficial.

Moreover, the benefits of the US Digital Coast are estimated to exceed costs by over 400%.

More details about these Cost-Benefit Analyses are available on page 55, in the Appendices.

Although there are special additional requirements in case of an MSDI due to the dynamic

and 3D marine environment, two of the six main types of SDI software tools, i.e., the Spatial

Database Management System and Catalogue/Registry & Metadata System, can most likely

be directly applied to MSDI, if the extremely large storage and dynamic data access

requirements can be fulfilled. This is because these systems can save data in any format, be

it multi-dimensional or not. It then depends on the query language and system performance

to allow multi-dimensional queries and near real-time dynamic access of data. Quantum GIS

worked very well, if some “bugs” are forgotten. Even in that case no data was lost and the

projects could be quickly run again after re-starting QGIS.

According to Halpern et al. (2012), there are at least five areas on the cutting edge of the

scientific work, which can benefit from the development of Marine SDI Tools and we can be

sure that the future GIS will make these kinds of analyses feasible:

Uncertainty: It is inherent to all information and it propagates through the system.

Temporal dynamics: In the ocean, species, people, currents, wind etc. etc. move.

Citizen science: To get more information than is possible by the authorities alone.

Big data integration: MSDI datasets must be assimilated for analysis and solution.

Spatial connectivity of processes: What happens in one place is affecting the others.

12.2 Shortfalls When using the GeoServer, there were often problems for example, when selecting “Layers

– Page 2”, which most of the time did not succeed and was giving an error message: “Sorry,

your session timed out... It looks like you waited too long to make that last change. If this

continues to happen, you should get in touch with your system administrator.” Login out and

in again did not always solve this problem, so there were not a time problem. In the opinion

of the writer, also the response times of GeoServer in the UCL configuration were

frustratingly slow for any efficient working, because clicking almost any item under the Data


40

menu, for example, resulted in waiting times of 2-25 seconds. Clearly, the GeoServer “was

waiting for local host” too often, which is probably not reflecting a problem in the

GeoServer itself, but in the UCL configuration. Due to the connection times, web mapping is

best suited to occasional usage and not so well for a professional or scientific utilization.

Sometimes GIS may give wrong impressions of how much may be done with it alone that

must be accounted. GIS is also not a real-time tool for dynamic monitoring yet. The marine

parameters are often changing rapidly, so mapping on the sea may be considered static only

in respect to land structures like islands, seafloor and bedrock, while for example water

level, temperature, currents, wind, chemical concentrations, species distribution etc. may

change rather in minutes or seconds than in days or years. Marine data repositories thus

need constant updating and the dilemma is that costly data then quickly becomes obsolete,

if not valueless. Still, it should be archived that multiplies the mass storage requirements.

Acquiring databases in the deep sea is difficult, because there isn’t available a technology

similar to Remote Sensing (RS) satellites that could be used to quickly acquire imagery over

large areas with a high-resolution. Currently about 90% of the oceans have still not been

mapped a single time. Even if we could do it once, then the high temporal repeat

requirement in three dimensions is making the task absolutely impossible today in any other

way than in a very low spatial (>km) and temporal (weeks-years) resolutions or in a small

Area of Interest (AOI). This problem may be partly solved by developing models to

interpolate in space and to extrapolate in time, giving useful estimates at least for the most

important Parameters of Interest (POI). An example of this is the prediction of marine

surface currents for shipping route optimisation in order to save fuel over long distances.

In case of INSPIRE SDI, where the data and its metadata are held in separate databases,

automatically updating the metadata, when data has been re-processed, requires the user

to save both of them on the local computer that is violating the philosophy of not making

multiple copies of the data. A software package called ER Mapper is a good example of not

making copies of large processed data files, but saving a script of processing steps that can

then later be repeated. Also, Ellul et al. (2013a) have shown using FOSS GIS software that

metadata and data can be tightly coupled so that modifying data automatically updates the

metadata.

For the integrity of data and metadata, it would be useful to save all the related information

in one file, although the INSPIRE directive appears to require that data and metadata are

saved separately in order to facilitate the data discovery through searching the metadata

that probably makes the data discovery quicker, because the metadata files are small in

comparison to the actual data files. The small file size also makes it easy to keep metadata.

On the other hand, the hardware and software infrastructure gets complicated, because the

different systems must be made to talk with each other instead of just simply downloading

an interesting data set. In the author’s opinion, integrating data and metadata in a single file

would greatly simplify the implementation of any SDI.


41

13 CONCLUSIONS In this project, it soon became evident that the subject of Spatial Data Infrastructures (SDI)

is huge. Moreover, Marine SDI (MSDI) has not yet taken a stance as well as the terrestrial

SDI, because the subject of MSDI is still new. Against these backgrounds, the author feels

that the MSDI Prototype presented in Figure 18 devolved somewhat elusive of necessity.

Nevertheless, a main result of this project was summarizing the principles, actors, policies,

technology, metadata, standards, services, data and geo-portals in Marine Spatial Data

Infrastructures. The study showed that there are lots of marine data the utilisation of which

is however not quite easy for a non-specialist. This may be changing thanks to Web Mapping

tools being developed at the same time, when datasets are being opened to the public.

It is crucial to recognize that while both GIS and Remote Sensing have made it possible to

make decisions based on facts during the last 20 years, it is also true to say that during this

period the overall situation with respect with aquatic environments has not improved

(Meaden, 2013). In fact, there is a high risk that mapping the Global Ocean and

implementing the initially well-meaning MSDIs may trigger a “gold rush” to marine minerals,

energy and the other marine resources with devastating consequences!

In case of the Ocean, four types of SDI software tools, i.e. the Desktop GIS Client, Desktop

Web GIS Development Toolkit, Web Map Server and Web GIS Server, must allow 3D if not

multi-dimensional and near real-time data be analysed as well as the related applications to

be developed and run. I.e., here it is absolutely necessary to keep in mind that the marine

environment is three-dimensional and in constant motion that is in contrast to for example

the land cover ashore.

Other special requirements of MSDI in comparison to SDI, are to be able to handle globally

extremely sparse, multi-resolution and multi-sensor data, where pixel resolutions are

varying from tens of kilometres down to centimetres, and sensors covering underwater

sonar depth and backscatter observations as well as satellite-based optical and microwave

oceanography and a myriad of point-type of observations of water chemical and physical

properties using buoys, for example. I.e., phenomena with largely varying nature are

investigated using many different Observation & Measurement (O&M) methods. Therefore,

MSDI should be able to handle three-dimensional, multi-temporal, multi-resolution and

multi-sensor datasets.

According to FAO (2003 and 2010) the shortest time and space scales are related to e.g.

beach waves, Langmuir waves (i.e., shallow, slow, counter-rotating vortices at the ocean’s

surface) and internal waves with scales ranging from a fraction of second to one day and

from 10cm to 1km, correspondingly. The longest time and space scales, on the other hand,

are related to zoo-plankton, eddies, fronts, adult fish, and ocean gyres with scales ranging

from weeks to over 10 years and from hundreds of meters to thousands of kilometres. I.e.,

very large ranges of temporal and spatial resolutions are required to analyse all kind of


42

dynamic marine information. If we have high-resolution, a lower resolution can always be

down-sampled, but a higher resolution cannot be up-sampled. This means that high

resolution should be the aim, as long as the ways of observation do not harm the animals.

It is of utmost importance to guarantee that the sound-waves required to map the deep

Ocean are not going to be too harmful to marine mammals, fishes and the other marine

animals. The sound is propagating underwater five times faster and over very much longer

distances than in the air, and many marine animals are sensitive to extremely low powers.

Today, the seas are polluted by noise originating from ships, construction and marine

exploration using both extremely low and high frequencies, and strong sounds, if not

explosions, in order to receive echoes deep under the seafloor in locating oil, gas and

minerals. It is quite evident that these and military tests are harmful for marine mammals,

as shown e.g. in the following video http://www.youtube.com/watch?v=O9gDk29Y_YY.

Healthy sane should be used regarding to exploration, experiments and operations at sea!

Because satellites can only acquire bathymetric grids above the sea surface with a very low

resolution (a few km) globally, as presented in Figure 41, on page 107, it will take a long

time before the deep waters have been mapped in detail by using maritime vessels. For the

same reason, the update rate is also much slower under the water than above. Besides

optical observations of a thin sea surface layer (due to visibility ranging from less than 1m to

up to 50m depending on turbidity and swell of the sea) there is no technology similar to the

Earth Observation (EO) satellites that could be used for mapping of large areas of deep

ocean quickly with a better than a few kilometres of resolution. A technological jump like,

for example, a larger number of unmanned, low-noise imaging sub-sea gliders is needed.

Today, dry land - covering less than 30% of the Earth - has been imaged using satellites

several times in a resolution of about 30m, but only 10% of the ocean bottom has been

mapped, in a much lower resolution. Track lines of hydrographic surveys done until 2010

with resolutions of 1 - 200m, depending on depth, are shown in Figure 38.

Currently, the best global map of the ocean depth, GEBCO Digital Atlas, has a resolution of

30 arc-seconds that corresponds to about 1km pixel spacing. It is based on a database of

ship track soundings interpolated (i.e., guessed) between the tracks and earlier bathymetric

grids (GEBCO, 2011). Even though the GEBCO Digital Atlas is a really great achievement

covering the entire globe, it is a quite rough and averaged Digital Elevation Model (DEM) of

the seafloor topography, missing not only most of the details between the 30 arc-seconds,

but all the other than geometric information and most notably, optical photography, when

compared to terrestrial satellite and e.g. Street View (Google Earth, 2013) observations.

The lack of detailed Global Ocean maps is a major limitation for an MSDI currently.

http://www.youtube.com/watch?v=O9gDk29Y_YY


43

14 FURTHER WORK In the opinion of the author, the most important next step would be to develop for QGIS or

Python a procedure in order to try systematically access the most important MSDI

warehouses and to make their data available first internal to UCL, and, then in the Web.

Currently, there are so many Marine Geoportals with so many data types that it can be

daunting to study any more than what is just needed in a quite specific area of science and

geography, of specific data type in a specific research project by an individual researcher.

A Python interface could access multi-dimensional data structures of marine SDI. CF has

grown from NetCDF, HDF etc. formats to make them more inter-operable being on a higher

level. These kinds of data formats should be investigated, if they could provide a working

method to integrate metadata and data, which are held separately in INSPIRE.

Integrating data and metadata in a single file could simplify the implementation of an SDI.

Therefore, it should be evaluated, if the separation is really bringing any advantages or not.

Starting on page 89 in the chapter of “Marine Geospatial Portals”, in the Appendices, there

are mentioned several good attempts to make marine information available, but are they

really interoperable and easy to use, having decision makers in mind, or, are they just large

collections of data, where each individual researcher is in any case required to spend lots of

time in order to understand the data types, formats etc., before being able to use the data?

Another issue for a study could be to investigate how Open Data could allow also Open

Science, where the data used in a research project would always be delivered with the

project report so that anybody could repeat the processes by just calling a script. And, then

being able to try own methods using the same dataset and tools.

MSDIs are bringing marine information available to decision makers, with the rational that

decisions should be based on understanding instead of cravings. But, what information is

important when deciding about the Ocean? Decision makers may not know. So, even if

there are a lot of good data, researchers must still select, analyse, visualise and explain it.

Last but not the least:

Please, explore the Ocean at

http://www.google.com/earth/explore/showcase/ocean.html# and

http://www.youtube.com/watch?v=A-zIiM6uAzE.

http://www.google.com/earth/explore/showcase/ocean.html

http://www.youtube.com/watch?v=A-zIiM6uAzE


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Steiniger, S. and Bocher, E., 2009. An overview on current free and open source desktop GIS

developments. International Journal of Geographical Information Science 23, pp.1345-1370.

Steiniger, S. and Hunter, A. J. S., 2009. Free and open source GIS software for building a

spatial data infrastructure. In E. Bocher and M. Neteler (Eds.): Geospatial Free and Open

Source Software in the 21st Century: Proceedings of the first Open Source Geospatial

Research Symposium, 2009, LNG&C, Springer, Heidelberg, pp. 247-261.

Steiniger, S., 2010. Building on Open Source GIS @ COSSFest 2010, presentation. Available

from: http://www.youtube.com/watch?v=-j7PLVJlvfE [Accessed 16 July 2013].

SYKE, 2013. The Baltic Sea Portal. Available from: http://www.itameriportaali.fi/fi/tutkimus/mertutk-

koordinaatio/fi_FI/koordinaatio/ [Accessed 7 August 2013].

UN, 1983. The Law of the Sea. United Nations Convention on the Law of the Sea.

UNESCO, 2008. IOC Workshop Report No. 206. Oostende,, UNESCO, 17 pp. Available from:

http://www.oceandatastandards.org/images/stories/ods_docs/wr206.pdf [Accessed 10 July 2013].

UNESCO, 2011. Ocean Data Standards. IOC Manuals and Guides 54, vol. 2, UNESCO, 19 pp.

UNESCO, 2013. Ocean Data Standards. IOC Manuals and Guides 54, vol. 3, UNESCO, 21 pp.

USGeo, 2012.GEOSS: the Global Earth Observation System of Systems. Group on Earth

Observations, 2 pages. Available from: http://www.masgc.org/pdf/masgp/07-012.pdf [Accessed 29

August 2013].

Vandenbroucke, 2012. Reporting cost/benefits of INSPIRE: Some thoughts from the INSPIRE

State of Play (SoP) and Drafting Team Monitoring & Reporting (DT MR) perspective. Spatial

Applications Division, KU Leuven, 25 pages.

http://www.smespire.eu/

http://geodiscover.cgdi.ca/wes/displayExternalLinks.do?identifier=C8375AA4-465E-A13C-D932-2DF25E190953&recordLocale=en_US

http://geodiscover.cgdi.ca/wes/displayExternalLinks.do?identifier=C8375AA4-465E-A13C-D932-2DF25E190953&recordLocale=en_US

http://www.ngdc.noaa.gov/mgg/fliers/97mgg03.html

http://www.youtube.com/watch?v=-j7PLVJlvfE

http://www.itameriportaali.fi/fi/tutkimus/mertutk-koordinaatio/fi_FI/koordinaatio/

http://www.itameriportaali.fi/fi/tutkimus/mertutk-koordinaatio/fi_FI/koordinaatio/

http://www.oceandatastandards.org/images/stories/ods_docs/wr206.pdf


53

VROM, 2008. GIDEON - Key geo-information facility for the Netherlands. Approach and

implementation strategy (2008-2011). Ministry of Housing, Spatial Planning and

Environment (VROM), 56 pages.

Ward, R., 2013. Global Geospatial Information Management and Marine Spatial Data

Infrastructures. Available from: http://www.hydro-international.com/issues/articles/id1451-

Global_Geospatial_Information_Management_and_Marine_Spatial_Data_Infrastructures.html [Accessed 24

July 2013].

Wright, D. (Ed.), 2013. Arc Marine v. 2.0. PPT presentation, Esri, 31 pages.

Wright, D. et al. 2007. Arc Marine. GIS for a Blue Planet. Redlands: ESRI Press, 202 pages.

http://www.hydro-international.com/issues/articles/id1451-Global_Geospatial_Information_Management_and_Marine_Spatial_Data_Infrastructures.html

http://www.hydro-international.com/issues/articles/id1451-Global_Geospatial_Information_Management_and_Marine_Spatial_Data_Infrastructures.html


54

16 APPENDICES

16.1 IHO S-100 Standard This is related to the 8.10 S-100 IHO Geospatial Standard for Hydrographic Data, on page 84.

Table 4. Parts of the IHO S-100 standard (IHO, 2009).


55

16.2 Cost-Benefit Analysis Most governments have started SDI initiatives and in the European Community, for

example, the cost of the Infrastructure for Spatial Information in Europe (INSPIRE) was

estimated in 2003 to be up to €273 million annually during a period of 10 years (INSPIRE,

2003). According to INSPIRE (2003, 2013) and Bregt (2012), the major portion of this cost is

required on a regional/ local level, as presented in Table 5 .

Table 5. INSPIRE annual requirements in million € as estimated in 2003.

EU National organisations Regional or local Total (M€)

2-6 13-27 77-240 92-273

Further according to Bregt (2012), the benefits on the regional/local level are the lowest,

while on the EU level they are the highest (as seen on Table 5). Because of this “reverse

pyramid effect” depicted in Figure 24 (Bregt, 2012, page 14), we may conclude that there is

a strong need to support the regional and local levels from both the EU and national levels.

Figure 24. Reverse pyramid effect (Bregt, 2012).

The INSPIRE costs are estimated to be divided between:

1. Metadata (20%)

2. Harmonisation of data (40%)

3. Network services (30%)

4. Training, learning and practicing (3%)

5. Monitoring & coordination of infrastructure construction (7%)

The percentages shown above are approximated from an early impact analysis and forecast

of INSPIRE costs in Poland between the years of 2009 and 2019 (Vandenbroucke, 2012).

It is, however, extremely difficult to do a reliable Cost-Benefit Analysis (CBA) for INSPIRE due

to the many influencing factors, interconnections and complications in estimating the

benefits that is probably explaining the ranges of variation between the CBA results by

different authors in Table 5. Only a few EU member states are reporting their INSPIRE costs,

the figures being between 10% and 30% depending on the type of the cost, i.e., metadata,

harmonization, network services, coordination and monitoring, as classified by Craglia and

Borzacchiello (2012).


56

Detailed case-studies accomplished in Catalonia 2007 and Lombardy 2008-2009 in any case

show quantitatively “clear benefits”, while CBA in the Netherlands 2009 shows benefits

being around two times the costs. Theoretical CBA studies have shown much higher benefit

to cost factors of up to 8 (Bregt, 2012, page 6). As a conclusion, today SDI appears to be

beneficial both financially and environmentally that is motivating its implementation.

The analysis of the US NOAA Digital Coast estimated benefits exceeding costs by over 400 %

over a 15-year period. Those cumulative costs and benefits accounted until now, i.e. for a

period from 2008 to 2012, are depicted in Figure 25. For example in 2011, the accounted

costs for that year were about $1,200,000 while the annual benefits at the same time were

nearly $5,400,000. “In FY2011 alone, 142000 users downloaded data and tools from the

Digital Coast, resulting in cost-reduction benefits that equal the entire historical investment

in the resource” (Adkins, 2012). Adkins measured efficiency gains in a straightforward way: If

a GIS technician who makes $36 per hour saves one hour of labour thanks to Digital Coast

that is a $36 benefit. And, if that happens tens of thousands of times each year, the

numbers simply add up.

Figure 25. Cumulative costs and benefits of the NOAA Digital Coast service during a 5 years’ period.

Reported benefits of INSPIRE enclose (Craglia and Borzacchiello; Cetl; Mäkelä, 2012):

1. Easier and better access to data and services

2. Data interoperability

3. Availability of new services and businesses

4. Improved data and service quality

5. Avoiding duplication and promoting re-use

6. Improved industrial and research efficiency

7. Removal of sharing barriers between organisations

8. Promoting inter-institutional collaboration

9. Money and time saving for users and authorities


57

10. Improved environmental assessment and decision making

Adkins (2009) considered six types of benefits of the NOAA Digital Coast:

1. Reduced labour costs as users find, download and apply data more rapidly.

2. Reduced technology costs due to smaller number of servers and IT staff members.

3. Avoided development costs, because Digital Coast already provides what is needed.

4. Reduced labour costs due to skills and training acquired through the Digital Coast.

5. Reduced costs as Digital Coast partners share labour skills and other investments.

6. Reduced cost when outreach by any one partner points to the products of others.

Craglia (2012) concludes in his study on INSPIRE Impact Assessment comparing the situation

in the year 2002 to that of 2009 that “in 2002 the most frequent problem was accessing data

and also in 2009 over half of the respondents had access problems”. In addition, data

integration, finding data and information on its quality were considered a problem in 2009.


58

16.3 Actors (Cont.) According to the Finnish national regulation (Finlex, 2009), authorities responsible for

managing spatial data related to the INSPIRE directive enclose the following:

- Agency of Rural Affairs http://www.mavi.fi/en/

- Centre for Economic Development, Transport and Environment http://www.ely-keskus.fi/en

- Finnish Defence Forces http://www.puolustusvoimat.fi/en/

- Finnish Energy Market Authority http://www.energiamarkkinavirasto.fi

- Finnish Environment Institute http://www.syke.fi/en-US

- Finnish Food Safety Authority http://www.evira.fi/portal/en/

- Finnish Forest Centre http://www.metsakeskus.fi/briefly-in-english

- Finnish Meteorological Institute http://en.ilmatieteenlaitos.fi/

- Finnish Museum of Natural History http://www.luomus.fi/english/

- Finnish Safety and Chemicals Agency http://www.tukes.fi/en/

- Finnish Transport Agency http://portal.liikennevirasto.fi/sivu/www/e/

- Finnish Transport Safety Agency http://www.trafi.fi/enLuonnontieteellinen

- Game and Fisheries Research http://www.rktl.fi/english/

- Geological Survey of Finland http://en.gtk.fi/

- National Land Survey of Finland http://www.maanmittauslaitos.fi/en

- METLA http://www.metla.fi/index-en.html

- Metsähallitus http://www.metsa.fi/sivustot/metsa/en

- Ministry of Agriculture and Forestry http://www.mmm.fi/en

- Ministry of Employment and the Economy http://www.tem.fi/en

- MTT https://portal.mtt.fi/portal/page/portal/mtt_en

- Municipalities of Finland http://www.localfinland.fi/en/Pages/default.aspx

- National Board of Antiquities http://www.nba.fi/en/index

- National Institute for Health and Welfare http://www.thl.fi/en_US/web/en

- Population Register Centre http://www.vrk.fi/default.aspx?site=4

- Statistics Finland https://www.tilastokeskus.fi/index_en.html

The highlighted authorities are as well working for the Finnish Marine Research Strategy,

the list of active participants of which is presented on the following page.

Active stakeholders in the Finnish Marine Research Strategy include (SYKE, 2013):

- Baltic Organisations Network for Funding Science http://www.bonusportal.org

- Central Union of Agricultural Producers and Forest Owners http://www.mtk.fi/en_GB/

- Centre for Economic Development, Transport and Environment http://www.ely-keskus.fi/en

- Confederation of Finnish Industries http://www.ek.fi/ek/en

- Finnish Association for Nature Conservation http://www.sll.fi/site-actions/english

- Finnish Environment Institute http://www.syke.fi/en-US

- Finnish Marine Scientist Association http://www.merentutkijat.fi

- Finnish Meteorological Institute http://en.ilmatieteenlaitos.fi/

http://www.mavi.fi/en/

http://www.ely-keskus.fi/en

http://www.puolustusvoimat.fi/en/

http://www.energiamarkkinavirasto.fi/

http://www.syke.fi/en-US

http://www.evira.fi/portal/en/

http://www.metsakeskus.fi/briefly-in-english

http://en.ilmatieteenlaitos.fi/

http://www.luomus.fi/english/

http://www.tukes.fi/en/

http://portal.liikennevirasto.fi/sivu/www/e/

http://www.trafi.fi/enLuonnontieteellinen

http://www.rktl.fi/english/

http://en.gtk.fi/

http://www.maanmittauslaitos.fi/en

http://www.metla.fi/index-en.html

http://www.metsa.fi/sivustot/metsa/en

http://www.mmm.fi/en

http://www.tem.fi/en

https://portal.mtt.fi/portal/page/portal/mtt_en

http://www.localfinland.fi/en/Pages/default.aspx

http://www.nba.fi/en/index

http://www.thl.fi/en_US/web/en

http://www.vrk.fi/default.aspx?site=4

https://www.tilastokeskus.fi/index_en.html

http://www.bonusportal.org/

http://www.mtk.fi/en_GB/

http://www.ely-keskus.fi/en

http://www.ek.fi/ek/en

http://www.sll.fi/site-actions/english

http://www.syke.fi/en-US

http://www.merentutkijat.fi/

http://en.ilmatieteenlaitos.fi/


59

- Finnish Port Association http://www.finnports.com

- Finnish Ship Owners Association http://www.shipowners.fi/en

- Finnish Transport Agency http://portal.liikennevirasto.fi/sivu/www/e/

- Geological Survey of Finland http://en.gtk.fi/

- Meriteollisuusyhdistys http://www.meriteollisuus.fi

- Metsähallitus http://www.metsa.fi/sivustot/metsa/en

- Ministry of Agriculture and Forestry http://www.mmm.fi/en

- Ministry of Defence http://www.defmin.fi/en

- Ministry of Education and Culture http://www.minedu.fi/OPM/?lang=en

- Ministry of Environment http://www.ym.fi/en-US

- Ministry of Foreign Affairs http://formin.finland.fi

- Ministry of Transport and Communications http://www.lvm.fi/web/en

- National Board of Antiquities http://www.nba.fi/en/index

- SCOR Committee http://www.academies.fi/english/committees/oceanic_research.html

- STUK http://www.stuk.fi/en_GB/

- University of Helsinki http://www.helsinki.fi/university/

- University of Oulu http://www.oulu.fi/english/

- University of Turku http://www.utu.fi/en

- VTT Technical Research Centre of Finland http://www.vtt.fi/?lang=en

- WWF Finland http://wwf.fi/en/

- Åbo Akademi University http://www.abo.fi/?lang=en

http://www.finnports.com/

http://www.shipowners.fi/en

http://portal.liikennevirasto.fi/sivu/www/e/

http://en.gtk.fi/

http://www.meriteollisuus.fi/

http://www.metsa.fi/sivustot/metsa/en

http://www.mmm.fi/en

http://www.defmin.fi/en

http://www.minedu.fi/OPM/?lang=en

http://www.ym.fi/en-US

http://formin.finland.fi/

http://www.lvm.fi/web/en

http://www.nba.fi/en/index

http://www.academies.fi/english/committees/oceanic_research.html

http://www.stuk.fi/en_GB/

http://www.helsinki.fi/university/

http://www.oulu.fi/english/

http://www.utu.fi/en

http://www.vtt.fi/?lang=en

http://wwf.fi/en/

http://www.abo.fi/?lang=en


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16.3.1 Customer Needs Spatial information is needed in general for policy and decision making, marine planning and

management, GIS, maritime traffic monitoring and applications within defined areas. Table

6 presents the major spatial boundaries defined in the Commonwealth legislation.

Table 6. Priority Commonwealth marine spatial information (Nairn, 2010).

Boundary Type Description Administrative boundaries

Coastal waters, territorial sea, contiguous zone, exclusive economic zone, ext. continental shelf, coral sea limits, baselines, base points, boundaries for treaty, petroleum and submerged land, petroleum lease, offshore mineral, reef, marine park, planning zone, world heritage, marine protected areas, fisheries, indigenous land and agreement, search and rescue, defence exercise, customs port limits, security port limits, immigration zone

Framework data

Shoreline, state borders, island reefs, rocks, cays, shoals, seas

Bathymetry

Bathymetric image, isobaths

Coastal and offshore gazetteer

Cultural locations, land features, marine features

Anthropogenic features

Historic shipwrecks, ocean disposal sites

Transport

Ship reporting locations, derived shipping lanes, ferry routes

Infrastructure

Petroleum wells, platforms pipelines, submarine cables, navigational aids

Geology

Seafloor features, sedimentary basins, tectonic elements

Environmental management

Bioregions, marine planning regions

In particular, customer needs are related to maritime safety, marine resources, coastal and

ocean environment, climate situation and weather forecast.

Frequently requested parameters enclose currents, sea-surface and air temperature, sea-

ice, sea level, surface winds, chlorophyll-dissolved oxygen, nutrients, PAR (light) and salinity

(MyOcean, 2013).


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16.4 National SDI Monitoring and Assessment MSDI monitoring and reporting is used to provide information on (IHO, 2011):

What datasets complete with metadata are being disseminated

Feedback from users and stakeholders

Definition of data, services and products being offered

A multi-view SDI assessment framework was developed by Grus et al. (2007) and it was

studied for assessing the goals of the Dutch national SDI (GIDEON) approved by the Dutch

government in 2008 (VROM, 2008). Being universal this method can be customised for the

purposes of any national SDI assessment. In general, the multi-view SDI assessment

framework contains the assessment requirements, approach, application and evaluation.

National SDI strategies are monitored while being constructed and used in order to justify

public spending on those SDIs. This can be done by formal progress reports assessing the

fulfilment of their goals related to SDI organizations and clearinghouses. Grus et al. (2007)

presented a chronological goal-oriented SDI assessment as follows:

Identify goals

Identify stakeholders

List indicators

Organise a workshop

Select and match indicators with goals

Formulate and apply the assessment for goal-oriented SDI

Evaluated results and improve earlier steps as needed

The GIDEON SDI policy on the other hand consists of 7 strategies, i.e.:

Giving spatial data a prominent place in the national e-services

Encouraging the use of key geo-registers

Implementing INSPIRE

Supporting standardization and national joint facilities

Stimulating the use of spatial data in crisis management, environmental protection,

mobility and spatial planning

Enabling industry to value-add public data as much as possible

Encouraging collaborative R&D&I to continuously develop the SDI facilities

The goal-oriented SDI assessment was applied to the Dutch GIDEON SDI with 4 goals. 21

Dutch organisations participated in the one-day workshop on goal-oriented SDI assessment

goals (Grus et al. 2007). They were given a rather exhaustive list of 72 indicators (or, suggest

their own) to select five per each GIDEON SDI goal with the following results, indicating the

most important indicators/properties of the national SDI geo-portal selected under each of

the 4 goals:


62

1. Spatial data about any location will be available for public and business users

- Web mapping service

- Map searching

- Number of visitors

- Number of datasets

- SDI searching

- Covering national territory

- Data providers and end-users are participating

2. Businesses can do value-adding to the spatial data provided by the government

- Freedom of geographic information through legislation

- Commercial pricing framework

- Private parties involved in NSDI strategic plan

- Data download service

3. Government will use the data

- Policy for sharing spatial information between public bodies

- SDI searching

- Covering national territory

4. There will be close collaboration between government, universities, institutes and

business in order to improve the SDI

- Public-private partnerships

- Long-term NSDI strategic plan

- Organizations agreeing the plan

- Open source services

- Data providers and end-users are participating

About half of the workshop participants considered the list of indicators be more than 50%

complete and, thus, improvements are needed in terms of the number of indicators and

thematic classification in order to make the selection complete and easier for the SDI

stakeholders. All the studied 72 indicators are listed in Grus et al. (2007, pages 16-18). Rix et

al. (2011) have made a comprehensive survey in Europe involving about 200 sub-national

SDIs from 26 countries.


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16.5 Free Open Source GIS Software (FOSS GIS) The term Free Open Source Software (FOSS) at the best means not only that it is free of

charge, but also that you’ll get the source code and may modify it as you like. Therefore, the

larger the particular FOSS community using, developing and testing is, the better and

broader the software. An active community is also vital for the future development. Public

domain FOSS belongs to everyone without restrictions, but there are also OSS software

packages with some restrictions, as noticed by Rodier (2010, pp. 6-7), when evaluating a

large number of OSS in his dissertation.

The data formats tested by Rodier (2010) enclosed ShapeFiles (.shp), Drawing Exchange

Format (.dxf), Text (.txt), OpenStreetMap (.osm), Image Disk (.img), ESRI grid, Tagged Image

File (.tif) and ASCII (.asc). Other tested features enclosed: connection to Web services (i.e.,

WMS, WCS, WFS), digitation, snapping, basic geo-processing (i.e., clipping, buffering,

intersecting, merging), connection to databases (i.e., tabular, relational, PostGIS), image

analysis (i.e., histogram, filtering, composition, segmentation), exporting, layout production

and measuring real distances. Most of the available FOSS GIS software packages are listed

on the following web pages:

- http://opensourcegis.org/

- http://freegis.org/

- http://web.sourceforge.com/

- http://www.osgeo.org/

- http://en.giswiki.net/wiki/Category:Software

- http://www.cascadoss.eu/en/index.php

- http://www.cascadoss.eu/en/index.php?option=com_content&task=view&id=14&Itemid=14

- http://en.wikipedia.org/wiki/List_of_GIS_software

- http://freegeographytools.com

- http://freegeographytools.com/2010/giscloud-an-online-geographic-information-system-application

Figure 26. Open source SDI software (Steiniger, 2010).

http://opensourcegis.org/

http://freegis.org/

http://web.sourceforge.com/

http://www.osgeo.org/

http://en.giswiki.net/wiki/Category:Software

http://www.cascadoss.eu/en/index.php

http://www.cascadoss.eu/en/index.php?option=com_content&task=view&id=14&Itemid=14

http://en.wikipedia.org/wiki/List_of_GIS_software

http://freegeographytools.com/

http://freegeographytools.com/2010/giscloud-an-online-geographic-information-system-application


64

16.5.1 Server Software Web Map Server software standards enclose (Steiniger, 2010):

- WMS for maps

- WSC for vectors

- WCS for raster data

- Proprietary equivalents: ArcServer, ArcIMS, AutoDesk MapGuide etc.

Web Map Server software development projects enclose:

- MapServer www.mapserver.org A strong product on standards.

- GeoServer www.geoserver.org A strong product on standards.

- AutoDesk MapGuide OSS www.mapguide.osgeo.org

- Degree www.wiki.deegree.org

- Quantum GIS web map server

- REST-based approaches

Web GIS Server software standards enclose (Steiniger, 2010):

- OGC WPS

- ISO 19119

- Proprietary equivalents: ArcServer, PCI Geomatics

Web GIS Server software development projects enclose:

- 52north WPS www.52north.or

- PyWPS www.pywps,wald.intevation.org Integrates with GRASS.

- Degree www.wiki.deegree.org

16.5.2 Spatial Database Management Systems SDBMS are mainly for storing spatial data enclosing following standards: (Steiniger, 2010)

- Extensions to existing products

- OGC SFS

- Proprietary equivalents: Oracle Spatial, ArcSDE, DB2 Spatial Extender

Spatial Database Management System development projects enclose:

- PostGIS www.reactions.net Strongest according to Steiniger,

2010.

- MySQL www.mysql.com

- SQLite www.gaia-gis.it/spatiallite

16.5.3 Catalogues/Registry & Metadata Catalogues are storing metadata, allowing discovery, browsing and query of data & services:

http://www.mapserver.org/

http://www.geoserver.org/

http://www.mapguide.osgeo.org/

http://www.wiki.deegree.org/

http://www.52north.or/

http://www.pywps,wald.intevation.org/


http://www.reactions.net/

http://www.mysql.com/

http://www.gaia-gis.it/spatiallite


65

- ISO 19115: Metadata

- ISO 19119: Geographic Services

- WSC for vectors

Software development projects enclose:

- GeoNetwork www.geonetworkopensource.net Supported by UN Food Agency.

- MDweb www.mdweb-project.org

- deegree www.wiki.deegree.org

16.5.4 Client Software Viewing, querying, creating, updating, analysing and printing.

Desktop GIS

- GRASS www.grass.osgeo.org “Legacy” software.

- gvSIG www.gvsig.org

- Quantum GIS www.qgis.org Developing quickly.

- OpenJUMP www.openjump.org

- MapWindow www.mapwindow.org Windows only software.

- uDig www.refractions.net Good on standards.

- Proprietary software are easier to use: ArcGIS, ArcExplorer, AutoDesk, Intergraph,

Bentley

Web GIS Development Toolkits

- Viewers: OpenLayers (Google Maps), OpenScales (Flex-based)

- Geoportal toolkits: MapBender, deegree

- Web map development toolkits: GeoMajas, GeoExt, GeoMoose, MapFish, SharpMap,

Google Web Toolkit, Google Gears etc.

- No single toolkit does it all, so some efforts required to put them together

- Proprietary software: ArcGIS Web Mapping APIs etc.

16.5.5 Summary Particularly competitive are (Steiniger, 2010):

- GeoServer & MapServer Web Map Server

- PostGIS DBMS

- GeoNetwork OpenSource Catalogue/Registry

- OPenLayers Web Map Viewer

- Web mapping toolkits

- Desktop GIS depends on tasks

- SDIs can be implemented using FOSS successfully

http://www.geonetworkopensource.net/

http://www.mdweb-project.org/


http://www.grass.osgeo.org/

http://www.gvsig.org/

http://www.qgis.org/

http://www.openjump.org/

http://www.mapwindow.org/

http://www.refractions.net/


66

In the opinion of the author, FOSS GIS is providing the general interoperability required to

be able to use an MSDI. For example, it is possible to download several GIS file formats

including shapefiles, which is the industry standard vector data format by ESRI/ArcView, you

can extract and reformat the data for loading for example into PostGIS, and then query and

browse metadata using psql or pgaccess, browse data graphically with QGIS and JUMP

analysing the downloaded data with GRASS or R and, finally, produce a high quality map for

publication using GMT.

16.5.6 Selecting FOSS Software 1. Use cases

2. Evaluation Criteria

3. Evaluation

4. Criteria Weighting

5. Selection

MySQL

MySQL is advertised to be “the world’s most popular open source database” and as “an

ideal choice for cloud-based database deployments” (MySQL, 2013). It is popular under

Linux Operating System (OS), but MySQL Database, MySQL Connectors and MySQL

Workbench are also available for Windows OS. For Excel, there is a new MySQL plugin

allowing easy manipulation of MySQL data without any prior MySQL technical knowledge.

For this reason, MySQL might suit very well for those UCL MSc courses using Excel by default

in course works.

Oracle Express

Oracle Express is a simplified version of Oracle Database 10g Release 2 RDBMS with

Oracle’s complete spatial functionality (Ellul, 2012).

PostgreSQL

PostgreSQL is an open source relational database management system (RDBMS) that has

been used by the Department of Civil, Environmental & Geomatic Engineering (CEGE) of the

University College London (UCL) in UK for developing a self-paced spatial database course

for CEGE’s Masters programmes in surveying, hydrographic surveying, remote sensing and

geographical information science (Ellul, 2012) with good results in that purpose. The support

for spatial objects to PostgreSQL is provided by its PostGIS extension.

PostGIS

PostGIS ads support for geographic objects to the PostgreSQL. “In effect, PostGIS spatially

enables the PostgreSQL server, allowing it to be used as a backend spatial database for

geographic information systems (GIS), much like ESRI's SDE or Oracle's Spatial extension”


67

(PostGIS, 2013). It is a spatial database for RS&GIS software enclosing the following software

packages (OpenGeo, 2013):

- Open Source Server: GeoServer, MapServer, Mapnik, DeeGree, SharpMap

- Open Source Desktop: GRASS, QGIS, uDig, gvSIG

- Proprietary Server: ArcServer, Ionic Enterprise, MapDotNet Server

- Proprietary Desktop: ArcGIS, Manifold, Safe FME, CadCorp SIS, MapInfo Professional

mezoGIS

mezoGIS is a graphical interface to query and analyse spatial data operating on external

PostGIS databases. mezoGIS provides a tool for geo-spatial analysis with PostGIS through

SQL queries. “There are other, excellent open source applications that can display PostGIS

datasets (like QGIS and GRASS). Those, however, expect properly indexed tables as an input,

and don't provide a built-in functionality to launch SQL queries. The focus of mezoGIS is to

stay close to the SQL workflow: Spatial queries are launched through manually entered SQL

commands, and results containing geometry are displayed as map layers” (mezoGIS, 2013).

Quantum GIS

Quantum GIS (QGIS) has an interface to GRASS GIS that is giving great technical potential in

the otherwise limited Remote Sensing (RS) and Earth Observation (EO) raster data

processing capabilities (Cascadoss, 2009). Chen et al. (2010) ranked QGIS the highest in their

evaluation (Ellul, 2010). As a dedicated GIS application, the technical potential of QGIS was

rated the best by Cascadoss (2009), although GRASS is even better among all the software

capable to GIS and/or RS. In addition, plug-ins for Python (Ellul, 2012) and an extensive

support for GIS data formats (Rodier, 2010; Steiniger, 2009) are available for QGIS.

Quantum GIS is offering two options for saving metadata: Users can create simple metadata

directly with the properties of each dataset, or, alternatively use metadata editor plug-in

called Metatools, which can access metadata in ISO19115 format (Ellul et al., 2013a).

GRASS GIS

The Geographic Resources Analysis Support System (GRASS) is used in geo-spatial data

management, data analysis, image processing, visualization, modelling and map production.

GRASS is a project of the Open Source Geospatial Foundation (OSGeo) and its development

has already lasted 30 years (GRASS GIS, 2013). According to Rodier (2010) GRASS is however

not quite user-friendly nor an easy to use software. But, it has a large user-base and its

functionality and usability were reported by Cascados (2009) to be clearly the best among

the OSS RS&GIS software packages, the nearest competitors being gvSIG and OSSIM.

uDig

uDig aims at providing a Java solution for a complete desktop GIS with analytical capabilities

being at the same time user-friendly and internet-oriented with geo-spatial web services

http://www.geoserver.org/

http://mapserver.org/

http://mapnik.org/

http://www.deegree.org/

http://www.codeplex.com/SharpMap

http://grass.itc.it/

http://www.qgis.org/

http://udig.refractions.net/

http://www.gvsig.org/web/

http://www.esri.com/arcgisserver

http://www.ionicsoft.com/

http://www.mapdotnet.com/

http://www.esri.com/arcgis

http://www.manifold.net/

http://www.safe.com/fme

http://www.cadcorp.com/

http://www.pbinsight.com/products/location-intelligence/applications/mapping-analytical/mapinfo-professional/


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(incl. WMS, WFS, WCS). It can use GRASS for complex vector operations and also embeds

JGRASS and Sextante plugins for advanced processing. In addition, uDig contains tools for

further plugin creation. Shapefiles, PostGIS, WMS and many other data formats are

supported. It is recommended by both Rodier (2010) and Chen et al. (2008) as a good

openGIS implementation that can sometimes be very slow, however.

SPRING

According to Rodier (2010), SPRING has a substantial set of tools aimed, for example, at

image segmentation, 3D, DEM and hydrological applications.

ILWIS

The Integrated Land and Water Information System (ILWIS) is a Remote Sensing (RS)

application and as such possibly not of immediate interest for GIS users. Its functionality,

usability and efficiency were the best among the dedicated OSS RS software packages

reviewed by Cascadoss (2009), although in terms of reliability, maintainability, portability

and web services it is lacking.

Geospatial Data Abstraction Library

Geospatial Data abstraction library (GDAL) is a programming library allowing manipulation

and format conversion of raster data. OGR comes with GDAL allowing the same for vectors

(Rodier, 2010).

GeoServer

The GeoServer is a full Java (J2EE) implementation of the OpenGIS Consortium's Web

Coverage Server (WCS) specification and Web Feature Server (WFS) specification together

with an integrated Web Map Server (WMS). I.e., there are three Services implemented:

1. Web Coverage Service (WCS) specification 1.0 and 1.1.1. All layers published by this

service are available on WMS also.

2. Web Feature Service (WFS) specification 1.0.0 and WFS 1.1.0, supporting all WFS

operations including Transaction.

3. A compliant implementation of WMS plus most of the SLD dynamic styling

extension. WMS can also generate PDF, SVG, KML and GeoRSS file formats.


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16.6 Metadata (Cont.) “Those responsible for the geo-processing needs of a governmental, commercial or industrial

organisation will find it useful to know the difference between catalogues and registries;

they will need to know about those catalogues that index their data and about those

registries that define their metadata” (Gould and Hecht, 2001).

Metadata is published in a metadata clearinghouse, also called a registry or repository

(Neiswender, 2010).

16.6.1 Metadata Classification Syntactic metadata describe what the data look like and how they are organized. Syntactic

fields often include the unique variable name, data type (integer, float, etc., including sizes),

file format, and units of measurement. Note that the first and last of these certainly have

semantic meaning, even if their primary use is for labelling or identification (Graybeal et al.

2010).

Semantic metadata describe what they mean. Semantic data are often considered to be

human-oriented rather than machine-usable, but that seems to be an assumption, and not

required by the term itself. Semantic fields are often more descriptive, such as long name,

definition, comments, and copyright. For example, the information that a field labelled

“SST” holds sea surface temperature measurements is semantic metadata. Most semantic

fields would be more widely useful if they followed agreed-upon conventions and

terminology. The increasing use of ontologies will likely push semantic content much more

into a machine-readable realm (Graybeal et al. 2010).

Search metadata, also known as discovery metadata, include information that would help a

person decide if there were things of interest in a data set or which search keywords to use

if they were using a data portal. An observation type such as multi-beam bathymetry is an

example of helpful search metadata, especially when managed by a system of controlled

vocabularies. Search metadata might also be latitude and longitude bounds, so that a

computer or a person could know if the data fell within an area of interest (Graybeal et al.

2010).

Use metadata helps a computer or a person to understand or process the data. Typical use

metadata would be calibration parameters, units, and precision information. Use metadata

often overlap with syntactic metadata, though they are not synonymous. Usage metadata

labels need to be unique to be of value for processing the data, while syntactic data may

not. Based on typical definitions of the terms, the distinction between use and search

metadata can be unclear. Some or all search metadata may be automatable, that is,

represented in ways that are meaningful to the applications processing and used by that

software. Indeed, this will be necessary to facilitate widespread data mining. Furthermore,

some use metadata will be of interest to people searching for data, even though it is more

oriented toward computer applications (Graybeal et al. 2010). When designing a metadata


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approach, it is important to consider both the terms and characteristics that people or

systems will need to search for and to find your data, and also the details that people and

systems would need to know to use them.

Static metadata are not expected to change much over the life of the data they describe,

even as the data evolve.

Dynamic metadata are conversely a function of the contents of the data, so as a dataset

evolves, dynamic metadata change. In reality, even static metadata may have to be changed

if, for example, incorrect information was captured and the error discovered later.

An interesting special case involves the seeding of metadata prior to the arrival of data

themselves. Metadata captured before data arrival are implicitly static and can be

associated with that data permanently, possibly as part of an automated process embedded

in the data stream. Metadata captured after data arrival imply some other process for

entering that information.

When planning your metadata process, it is worth considering which metadata you expect

to be persistent through time, and which will need to change. And you will need to

determine the processes for updating dynamic metadata, and for handling an unexpected

need to adjust or correct static metadata (Graybeal et al. 2010).

Shankaranarayanan and Even (2006) propose six types of metadata based on their function:

Infrastructure metadata describes the components of the computer systems, such as

hardware, operating systems, networking and database servers. It is primarily used

for system maintenance.

Model metadata (the data dictionary) describes the modeling of data into entities

and their relationships (e.g., tables and column headers). It includes conceptual,

logical, and physical descriptions as well as semantic information, such as terms used

and how they relate to other terminology in the system.

Process metadata provides information on how data are generated and the changes

they undergo from source to target.

Quality metadata includes both a description of the physical size (number of records,

bytes) as well as quality measurements, such as the accuracy and completeness of

the data.

Interface (delivery and reporting) metadata captures how the data is used, such as

where and how much data are delivered (e.g., downloaded from an online system)

and in what formats. It can also include how the data are used in derivative products

like reports.

Administration metadata includes information on users, security, and access

privileges to data and applications.


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16.6.2 Metadata Template To publish your metadata, a metadata template needs to be designed or filled-in based on

available standards and, then, it is converted into an electronic format suitable for

publishing in the metadata clearinghouse, that is, registry. A comma separated value text

file (CSV ASCII) and Extensible Markup Language (XML) are versatile text-based formats that

many standards are adopting (Neiswender, 2010). It is however not always clear, if

particular information is data or metadata. For example, coordinates could be either data or

metadata. To clarify the separation, Graybeal et al. (2010) have given these three examples:

1. Data: Photo of a newly discovered species of fish

Metadata: Location of discovery (latitude, longitude, depth), other fish in the area,

salinity of the water, quantity discovered (school, single fish or larger number) etc.

2. Data: Meteorological Measurements

Metadata: Location of readings (latitude, longitude, height), instrumentation used to

collect data, units, processing done to measurements etc.

3. Data: Sediment Core Record

Metadata: Location of discovery (latitude, longitude, depth), description of

stratigraphy, length, type of coring device etc.

I.e., there may be some standard fields, like location and date. But, in general, different

dataset require different types of descriptions. For this reason, a metadata template must

be created that fits your particular data. Some standards enclose sample templates

(Neiswender, 2010). In any case, you need to develop a working list of metadata elements

by using an Excel table or a graphical map done with the help of the Freemind software of

which Figure 27 shows an example.

Figure 27. Freemind graphical approach to define a list of metadata elements (Neiswender, 2010).

Examples of how to write good metadata can be accessed at the following web page:

https://marinemetadata.org/guides/mdataintro/mdataexamples.

https://marinemetadata.org/guides/mdataintro/mdataexamples


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16.7 Standards (Cont.) “Problems related to the existence of scattered data, lack of existing data, outdated data,

formats and different characteristics to storage, among others, hinder the widespread use

and interoperability of SDI” (Souza and Delgado, 2012).

Potential technical problems have been arisen due to immature technical standards, pricing,

access and use licensing, copyright, trade secret, security etc. issues, political consent

regarding e-services, lack of coordination in governance between countries and

organizations, varying data quality. And, all the problems mentioned, are matters of

agreement to be cleared away by standardisation. A true technical problem, however, is

that there are very large white areas in the map of the Ocean in comparison to land maps.

16.7.1 Marine Metadata Standards A metadata standard specifies how to describe a dataset. There are content standards and

format standards. By carefully articulating how the metadata elements are named,

structured, and utilized, metadata standards enable interoperability and allow for the

creation of tools to work with the metadata, such as searchable repositories and metadata

creation templates (Neiswender et al., 2011).

16.7.1.1 Content Standard

Content standards are describing the information to be acquired by giving each metadata

element a label (i.e., a name) and its definition. For example, “vessel” is a label for a

common oceanographic metadata element. The definition could contain the name of the

research vessel possibly appended with the particular item from the ICES list of ship names.

The content standard also requires statements of usage for the metadata elements. For

example, a rule might specify mandatory elements (Neiswender et al., 2011).

16.7.1.2 Format Standard

Format standards express how the information described in content standards will be

represented. Common formats enclose NetCDF, XML, HTML and ASCII text, the purpose of

which is to allow machine readability of metadata. For example, the ISO 19139 contains

both the content and format standards.

16.7.1.3 Marine Community Metadata Profile of ISO 19115

The Marine Community Profile of ISO 19115 standard was developed by the Joint Facility

Australian Oceanographic Data Centre. In addition to all ISO 19115 core and mandatory

metadata elements, it covers the sea-going collection of oceanographic datasets with four

new metadata elements (items 1-4 below) and two new code tables (Neiswender et al.,

2011; AODC, 2013):

1. Revision data of metadata.

2. Sampling frequency: daily, weekly, monthly.

3. Temporal currency of the resource, describing values in the Currency Type Code list.


73

4. Temporal Aggregation of the resource with the Temporal Aggregation Unit Code list.

5. Currency Type Code describing the temporal currency: historical, predicted etc.

6. Temporal Aggregation Unit Code: day, month, multi-month etc.

In addition, an XML encoding schema based on ISO19139 has been developed to describe,

validate and exchange Marine Community Profile metadata (AODC, 2013).

The Marine Community Profile can be downloaded at the following web address:

http://www.aodc.org.au/files/MarineCommunityProfilev1.4.pdf.

16.7.1.4 Metadata Entry and Search Tool

BlueNet (www.bluenet.org.au) has developed the Metadata Entry and Search Tool (MEST) for

marine datasets. The MEST application can be downloaded from the BlueNet wiki at

http://bluenetdev.its.utas.edu.au/download/bluenetmest.html.

16.7.1.5 Ocean Data Standards Pilot Project

IODE (International Oceanographic Data and Information Exchange) and JCOMM (Joint

WMO-IOC Technical Commission for Oceanography and Marine Meteorology) recognized

that there were not agreements on a wide range of matters to allow easy exchange of

collected data. Therefore, the Ocean Data Standards Pilot Project (Intergovernmental

Oceanographic Data and Information Exchange) was established in 2008. There were several

recommendations and improvements including the following (UNESCO, 2008, 2011, 2013):

- ISO 8601 standard as standard representation of date and time

- IODE Quality Flag Standard for oceanographic and meteorological data

- ISO-6709 standard for latitude, longitude and altitude

- ISO-3166 for country codes

- Platforms

- Quality control of temperature, salinity, sea-level, currents, surface waves,

- Projects, institutions, units, instruments, science words, taxa, parameters,

16.7.1.6 FGDC CSDGM Metadata Profile for Shoreline Data

The Shoreline Metadata Profile is an extension to the existing FGDC (US Federal Geographic

Data Committee) Content Standards for Digital Geospatial Metadata (CSDGM). It allows

describing shoreline data for GIS applications including national mapping. Important

application areas include coastal zone management, environmental monitoring, exploration,

resources utilization, legal and jurisdictional issues, ocean and meteorological modeling,

engineering, construction, planning, and many others (FGDC, 2001).

Additional terms and data elements are provided to support shoreline and coastal

metadata. The added elements include tidal (i.e. type and time) and weather (i.e., wind

speed and direction, wave height and barometric pressure) conditions, as well as

environmental events, like hurricanes (AODC, 2013).

http://www.aodc.org.au/files/MarineCommunityProfilev1.4.pdf

http://www.bluenet.org.au/

http://bluenetdev.its.utas.edu.au/download/bluenetmest.html


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16.7.2 International Organization for Standardization (ISO) The committee currently has 66 published standards including those listed in the table

below, and, others related to e.g. HTML, XML, SVG, SOAP and WSDL.

Standard Description ISO 6709 Representation of geographic point location by coordinates

ISO 19101 Geographic information reference model

ISO 19103 Conceptual schema language

ISO 19104 Terminology

ISO 19105 Conformance and testing

ISO 19106 Profiles

ISO 19107 Spatial schema

ISO 19108 Temporal schema

ISO 19109 Rules for application schema

ISO 19110 Methodology for feature cataloguing

ISO 19111 Spatial referencing by coordinates

ISO 19112 Spatial referencing by geographic identifiers

ISO 19113 Quality principles

ISO 19114 Quality evaluation procedures

ISO 19115 Metadata

ISO 19116 Positioning services

ISO 19117 Portrayal

ISO 19118 Encoding

ISO 19119 Services

ISO 19120 Functional standards

ISO 19121 Imagery and gridded data

ISO 19122 Qualification and certification of personnel

ISO 19123 Schema for coverage geometry and functions

ISO 19125 Simple feature access

ISO 19126 Feature concept dictionaries and registers

ISO 19127 Geodetic codes and parameters

ISO 19128 Web map server interface

ISO 19129 Imagery, gridded and coverage data framework

ISO 19130 Imagery sensor models for geo-positioning

ISO 19131 Requirements for application schema and feature catalogue

ISO 19132 Reference model

ISO 19133 Tracking and navigation

ISO 19134 Multimodal routing and navigation

ISO 19135 Procedures for item registration

ISO 19136 Geography Markup Language (GML)

ISO 19137 Core profile of the spatial schema

ISO 19138 Data quality measures

ISO 19139 Metadata - XML schema implementation

ISO 19141 Schema for moving features

ISO 19142 Web Feature Service (WFS)

ISO 19143 Filter encoding

ISO 19144 Classification system structure & Land Cover Meta Language (LCML)

ISO 19145 Registry of representations of geographic point location

ISO 19146 Cross-domain vocabularies


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ISO 19148 Linear referencing

ISO 19149 Rights expression language for geographic information (GeoREL)

ISO 19150 Ontology Framework

ISO 19152 Land Administration Domain Model (LADM)

ISO 19155 Place Identifier (PI) architecture

ISO 19156 Observations and measurements

ISO/IEC 9075 Structured Query Language (SQL)

The official contents of ISO/TC 211 standards on geographic information can be accessed at

http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_tc_browse.htm?commid=54904&pu

blished=on&includesc=true.

The two other relevant geospatial standards, when implementing SDIs are ISO TC 204 and

JTC-1 dealing e.g. with road transportation and catalogues/registries, correspondingly.

16.7.3 Open Geospatial Consortium (OGC) The Open Geospatial Consortium (OGC) develops standards to make spatial data and

services interoperable. The OpenGIS Simple Features Access (SFA) standard is also called ISO

19125. The SFA Part 1 describes the geometry of simple geographic features, like Point,

Curve, Surface and collections of them by using Universal Markup Language (UML). SFA Part

2 defines a Structured Query Language (SQL) supporting, among others, querying of those

simple features, which can have both spatial and non-spatial attributes. In SQL, each feature

is occupying a row in the feature table. Also CORBA (Common Object Request Broker

Architecture) and OLE (Object Linking and Embedding) are used.

The following standards are indispensable for the application of SFA: ISO 1907, ISO 19109,

19111, ISO 19119, ISO 19133, ISO/IEC CD 13249-3:2006 and ISO/IEC 9075 (Herring, 2011).

OGC standards relevant to SDI enclose (Steiniger, 2010) the following, of which the

underlined are the most commonly used (Nebert, 2013):

Data delivery

o OGC Web Map Service (WMS)

o OGC Web Feature Service (WFS)

o OGC Web Coverage Service (WCS)

Data formats

o OGC Simple Feature Standard (SFS)

o OGC Geography Markup Language (GML)

o Keyhole Markup Language (KML)

Data search

o OGC Catalogue Service (CSW)

o Gazetteer Service (WFS-G)

Other purposes

http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_tc_browse.htm?commid=54904&published=on&includesc=true

http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_tc_browse.htm?commid=54904&published=on&includesc=true


76

o Web Processing Standard (WPS)

o Coordinate Transformation Service (CTS)

o Web Terrain Service (WTS)

o Styled Layer Descriptor (SLD)

o OGC Web Map Context (WMC)

There are over 30 OGC working groups of which those two directly related to Marine SDI are

briefly presented below. All the working groups can be accessed at the follow web page:

http://www.opengeospatial.org/projects/groups/wg

16.7.3.1 Hydrology Working Group

The OGC Hydrology Domain Working Group (DWG) is addressing relationships between

spatial information (features) and observational data (O&M). Relevant ISO and OGC

standards to the Hydrology DWG include:

Table 7. Standards relevant to the OGC Hydrology Domain Working Group.

Standard Description

GML Encoding standards for geospatial and technical data

WFS Interface for hosting and accessing feature data

O&M Observation & Measurement metadata and results

SOS Interface for hosting and accessing observation data

SPS Interface for tasking observational sensors

WCS Interface for hosting and accessing gridded data and time-series

ISO 19115 Metadata for datasets: Description of geographical information and associated services, including contents, spatial-temporal purchases, data quality, access and rights to use.

ISO 19119 Metadata for web services: Supports the description of geo-spatial services including data portals, web mapping applications, data models and online data processing, in conjunction with ISO 19115 (FGDC, 2013).

ISO 19139 Metadata XML schema implementation: Specifies the ISO 19115 metadata record format and general content, description validation and metadata exchange.

In order to apply these OGC and ISO standards to the water resources domain, they need to

be profiled appropriately (Hydrology DWG, 2013).

16.7.3.2 MetOcean Working Group

In order to achieve interoperability in using spatial information, a range of OGC standards

such as WMS, WCS, GML, WFS, as well as data processing and sensor related services need

to be implemented in the applications. Also the following requirements are listed by

MetOcean DWG (2013):

Climate Science Modelling Language (CSML) for encoding climate, atmospheric and

oceanographic data: http://csml.badc.rl.ac.uk/

http://www.opengeospatial.org/projects/groups/wg

http://csml.badc.rl.ac.uk/


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ncML-GML extension of the netCDF Markup Language (ncML) for facilitating

interoperability between the atmospheric and GIS data systems:

http://www.ogcnetwork.net/node/214

Weather Information Exchange Models (AIXM & WXXM):

http://www.wxxm.aero/public/subsite_homepage/homepage.html

Metadata for Climate Models (METAFOR):

http://external.opengeospatial.org/twiki_public/MetOceanDWG/MetaFor

Weather Objects Modelling Language (WOML) for defining meteorological

phenomena by using GML Feature model and the basis of the language:

https://agora.fmi.fi/display/WOML

ISO/DIS 19156 - Observations and Measurements (O&M):

http://www.iso.org/iso/home/store/catalogue_tc/catalogue_detail.htm?csnumber=32574

NetCDF (network Common Data Form) supporting the creation and sharing arrays of

scientific data: http://www.unidata.ucar.edu/software/netcdf/

Climate & Forecast (CF) Metadata Convention for sharing of files created with the

NetCDF API (i.e., Application Programming Interface) : http://cf-pcmdi.llnl.gov/

WMO International Codes: http://www.wmo.int/pages/prog/www/WMOCodes.html

The ISO/DIS 19156 Geographic Information - Observations and Measurements standard is

considered to form the basis of the conceptual model for meteorology and oceanography

(MetOcean DWG, 2013).

16.7.4 S-100 IHO Geospatial Standard for Hydrographic Data The S-100 standard will eventually replace the S-57 IHO Transfer Standard for Digital

Hydrographic Data. Therefore, S-57 is not further discussed in this dissertation.

The S-100 IHO Hydrographic Geospatial Standard for Marine Data and Information is based

on the ISO 19100 and conforms to the ISO TC 211 geographical information standards as far

as possible. S-100 specifies (IHO, 2009):

1. Registers of information related to hydrography

2. Products, feature catalogues and a definition of the feature model

3. Use of data and metadata for hydrographic requirements

The S-100 standard covers items such as: 3D, time-varying data, gridded data, bathymetric

products, inland ENC (Electronic Navigational Chart), nautical publications, MIOs (Marine

Information Overlays), Web Services and next generation S-101 ENC.

S-100 consists of total 16 parts, which are listed on page 54 in the Appendices with

associations to the ISO 19100 standard.

http://www.ogcnetwork.net/node/214

http://www.wxxm.aero/public/subsite_homepage/homepage.html

http://external.opengeospatial.org/twiki_public/MetOceanDWG/MetaFor

https://agora.fmi.fi/display/WOML

http://www.iso.org/iso/home/store/catalogue_tc/catalogue_detail.htm?csnumber=32574

http://www.unidata.ucar.edu/software/netcdf/

http://cf-pcmdi.llnl.gov/

http://www.wmo.int/pages/prog/www/WMOCodes.html


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16.7.5 INSPIRE The Inspire is being built on the infrastructures established by the EU member states aiming

to make those national SDI systems compatible and usable in co-operation. The data and

services from the Galileo satellite positioning and Global Monitoring for Environment and

Security (GMES) systems should be used. The Inspire directive applies to public authorities,

but also others should take the advantage of it on a voluntary basis.

1. Coordinate reference systems (x,y,z)/(lat,lon,h) coordinates based on geodetic h and v datum.

2. Geographical grid systems Multi-resolution grid with origin, orientation and cell size.

3. Geographical names Area, region, locality, city, town or other feature of interest.

4. Administrative units Local, regional or national governance separated by border.

5. Addresses Road name, house number, postal code etc.

6. Cadastral parcels Area in cadastral register or similar.

7. Transport networks Road, rail, air, water network or related infrastructure.

8. Hydrography Marine area, water body, river basin or related item.

9. Protected sites Area of specific conservation.

10. Elevation DEM of land, ice or ocean surface incl. bathymetry & shoreline.

11. Land cover Natural or artificial cover incl. forest, agriculture, water etc.

12. Ortho-imagery Geo-referenced imagery of the Earth.

13. Geology Structural composition, bedrock, aquifer and geomorphology

14. Statistical units Units described by statistics.

15. Buildings Building location.

16. Soil Depth, structure, content, erosion, slope, water capacity etc.

17. Land use Residential, commercial, recreational, industry, forest, rural etc.

18. Health and safety Pathology/health distribution linked to pollution/environment.

19. Utility and governmental services Sewage, waste management, energy, water, schools, hospitals.

20. Environmental monitoring facilities Measurement of emissions and ecosystem parameters.

21. Production and industrial facilities Industrial sites with pollution prevention, mining, storage etc.

22. Agricultural and aquaculture facilities Farming incl. irrigation system, greenhouse and stable.

23. Population distribution Geographical population characteristics.

24. Area management zones and units Dumping site, drink water, water fairways, mining, ICZM etc.

25. Natural risk zones Atmospheric, hydrologic, seismic, volcanic, fire etc. hazards.

26. Atmospheric conditions Physical atmospheric conditions measured.

27. Meteorological geographical features Weather measurements, rain, temperature, wind etc.

28. Oceanographic geographical features Physical conditions, currents, salinity, temperature, waves etc.

29. Sea regions Sea divided into regions of common physical conditions.

30. Bio-geographical regions Homogeneous ecological conditions regions.

31. Habitats and biotopes Geographical, ecological conditions, abiotic/biotic features etc.

32. Species distribution Geographical of animal or plant species.

33. Energy resources Hydrocarbon, hydropower, bio-energy, solar, wind etc. extent.

34. Mineral resources Metal ores, minerals incl. depth information on the resource.

INSPIRE insists data to be kept up to data by the original data provider or a custodian that is

very useful in order to avoid multiple versions of same data to appear in addition to keeping

the data current. But, when it is further insisted by INSPIRE that the data should be not

duplicated, it has according to the author of this dissertation a counter-productive effect

making the data utilization extremely slow in comparison to accessing a local copy, because

the data must be transferred every time, when starting a new GIS analysis session, for

example. The typical internet transfer rates are currently much slower than the transfer

rates in a local computer or network. Therefore, the data must be copied in order to work


79

with it without needing to wait minutes of WMS accesses time. Secondly, what would

happen, if the network would be down? Then, of course no WMS service or data would be

available to work with.

Each EU member state has usually a public authority as an Inspire contact point. Every three

years starting in 15 May 2013, member states shall report to the European Commission how

their public sector SDI is coordinated, how quality assured, what is authorities’ contribution

to SDI, how SDI is used, what data sharing agreements there are between public authorities,

and what are the costs and benefits of implementing the Inspire directive.

16.7.6 World Wide Web Consortium (W3C) W3C4 is an open international organization whose goal is to lead the World Wide Web to its

full potential by developing common protocols. W3C open standards support the

development of technologies for advancing the Internet by ensuring interoperability, such

as extensible Markup Language (XML) [2], Resource Description Framework (RDF) [3],

Ontology Web Language (OWL) [4], web services [5], etc.

16.7.7 European Committee for Standardization (CEN) CEN aims at developing European Standards and other technical specifications. CEN/TC 287

is specialized in geographic information. CEN/TC 287 developed standards for

interoperability of metadata, services and encoding, among others.

16.7.8 Registries and Repositories Interoperability is achieved by allowing information models and service definitions be

shared. A registry is used to publish these objects. According to ISO 19135, a registry is an

information system, whilst a register is a set of files.

16.7.8.1 ISO 19135

The ISO 19135 standard specifies how to establish registers of uniquely, unambiguously and

permanently assigned to geographic information. The standard specifies what is necessary

to provide identification and meaning to the registered items.

16.7.8.2 IHO Hydrographic Registry

The IHO Geospatial Information Infrastructure is being developed. The core component of

this will be the S-100 Geospatial Standard for Hydrographic Data and its associated

information registry. IHO Feature Dictionary registers: http://195.217.61.120/iho_registry.

16.7.8.3 DGIWG Feature and Attribute Data Registry

The Digital Geospatial Information Working Group (DGIWG) component registers including

the DGIWG Feature Data Dictionary (FDD) Register. FDD contains geographic information

concepts to characterize real world phenomena based on the Feature and Attribute Coding

Catalogue (FACC) which is a component of the Digital Geographic Information Exchange

Standard (DIGEST).

http://195.217.61.120/iho_registry


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16.8 Services (Cont.)

16.8.1 Atom Syndication Format (Atom) Atom is an XML-based list of feeds information composing of entries with a set of related

metadata. The primary use of Atom is to collect Web content such as weblogs and news

headlines to Web sites.

16.8.2 Web Authentication Service (CAS) The Central Authentication Service (CAS) involves a client web browser, web application and

the CAS server, permitting web applications to authenticate the user without getting access

to e.g. user’s password.

16.8.3 Catalogue Service (CSW) The OGC CAT standard provides the ability to publish and search collections of descriptive

information, i.e., metadata, for data, services and related information. Metadata may be

queried by humans or computer (OGC, 2013).

16.8.4 Web Coordinate Transformation Service (WCTS) The OGC Coordinate Transformation (CT) is a standard way of coordinate transformations

with the aim that that all spatial data are defined in the same spatial reference system.

16.8.5 NetCDF Climate and Forecast (CF) The NetCDF library (NetCDF) is intended to access climate, atmosphere, surface, and ocean

data according to well-defined rules. Sufficient metadata should make it self-describing in

the sense that each variable is described in time and space. This convention enables

software to display data and perform operations with minimal user intervention.

16.8.6 Web Coverage Service (WCS) The OGC WCS standard provides access to coverages representing space-varying

phenomena that relate a spatio-temporal domain to a multi-dimensional range of

properties.

16.8.7 Web Feature Service (WFS) The OGC WFS standard provides access to and management of a feature data repository.

Rather than sharing geographic information at the file level using File Transfer Protocol

(FTP), for example, the WFS offers direct access to geospatial information.

16.8.8 Web Map Print Service (WMPS) WMPS is a service for creating high quality map prints.


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16.8.9 Web Map Service (WMS) The OGC WMS standard provides facilities for the creation and display of map views of

geographic information that is generally rendered in a pictorial format such as PNG, GIF or

JPEG, or in a vector form.

16.8.10 Web Map Tile Service (WMTS) OGC WMTS server applications can serve map tiles of spatially referenced data using tile

images with predefined content, extent and resolution.

16.8.11 Web Perspective View Service (WPVS) WPVS aims at portrayal of 3D geo-information of e.g. virtual city and terrain models.

16.8.12 Web Processing Service (WPS) The OGC WPS interface standard provides input and output rules for geo-spatial processing

services, such as polygon overlay. It also defines an interface that facilitates the publishing

of geo-spatial processes and discovery of those processes.

16.8.13 Web Security Service (WSS) The OASIS WSS specification describes enhancements to SOAP messaging in terms of

integrity and confidentiality allowing a wide variety of data security and encryption.

16.8.14 Sensor Observation Service (SOS) The OGC Sensor Observation Service (SOS) allows sensor data to be managed in an

interoperable way. Querying observations, registering new sensor and inserting new sensor

observations are provided.

16.8.15 Symbolization (SLD) The OGC Styled Layer Descriptor (SLD) allows user-defined symbolization and coloring of

geographic data.


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16.9 Data (Cont.) National Hydrographic Offices (HO) can be seen as the competent authority to provide

hydrographic data in SDI (IHO, 2011). HO data commonly enclose physical features of the

seabed and coast, as well as general water levels, tides and currents. These data are

provided for the safety of navigation and environmental protection, but also more and more

for maritime spatial planning, engineering of marine infrastructures and exploration of

energy, mineral and other natural resources.

Despite the protection of environment is considered of high importance for example by the

INSPIRE directive, it is quite evident for the time being that the more information there will

be about potential marine resources, the more they will be commercially exploited and the

more will the environment suffer. Therefore, environmental protection will get more

difficult with increasing information on the seabed. No information and no human

interference would of course be the ideal situation for the natural environment – to say it

straight – because, from the human point of view, commercial exploitation of marine

resources weight more than protecting the marine life.

HO data forms the basis for any MSDI comprising of source or raw data including dense

bathymetric and other hydrographic datasets, and product data including Electronic

Navigation Charts (ENC), Digital Elevation Model (DEM), seafloor classification, coastline,

maritime borders, digital nautical documents and data about data, i.e. metadata.

In addition, metadata for data discovery needs to describe the type of data (to enable users

to apply the data correctly), the extent, quality, horizontal and vertical datum and projection

as well as temporal reference. Use of the ISO 19115 standard is applied for interoperability.

Although searching for metadata by type, area and keyword can be simply provided on a

website or even on paper, searching through an SDI/MSDI portal is ideal for efficiency and

automation purposes. In the opinion of this author, searching by area is optimal, when the

geographical Area of Interest (AOI) is specified. But, sometimes the user may want to find

out, if specific type of data is available and where, making the other search types preferable.

After investigating the metadata and finding the right data, the user wants to download it.

Via Web Mapping Services (WMS), automated search and download can be developed. For

the most efficient data processing, the data may be downloaded on the local hard disk,

where it can be accessed immediately, repeatedly and processed much quicker than

through a common web mapping service is possible. Although the data may be copied many

times, the original source of data will always stay the same and will be accessed, when local

data needs to be updated. Mobile web mapping services may be based on visualisation of

readily processed datasets and then the raw data does not need to be copied.


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16.9.1 Land Use

16.9.2 Surveillance & Exploration

16.9.3 Oil & Gas

16.9.4 Mineral Extraction

16.9.5 Renewable Energy

16.9.6 Fishing & Mariculture

16.9.7 Construction, Dredging & Disposal

16.9.8 Infrastructure & Submarine Cables The primary use of the Atlantic Submarine Cable and Pipeline Database is for reference on

Canadian Hydrographic Service (CHS) products and an effort to track cable positions for the

purposes of stakeholders, marine safety, hazard assessment and project planning. Latitude

and longitude positions for cables pipelines are stored (Smith, 2012).

16.9.9 Marine Recreation & Tourism

16.9.10 Conservation Areas, Species Habitats and Wrecks The purpose of the Nova Scotia Wetlands and Coastal Habitats Inventory in Canada is to

delimit wetland and coastal habitat areas for conservation and sustainable use. Parameters

recorded enclose dominant wetlands and coastal habitats greater than 0.5 hectares

including bogs, fens, deep and shallow marshes, seasonally flooded flats, meadows, shrub

and wooded swamps, lakeshore wetlands, salt marsh, saline ponds, dunes, beaches, cliffs,

and, estuarine and marine flats. These habitats are recognized being ecologically,

economically and socially important ecosystems to support policy and legislation, land use

planning, impact assessment, environmental monitoring, reporting and scientific research

(Milton, 2010).

The Living Marine Legacy of Gwaii Haanas I lists all marine plant species and maps their

distributions from the first records in 1911 to 1999, including 348 seaweed and 4 sea-grass

species from 456 intertidal to shallow sub-tidal locations. The database covers the Haida

Gwaii archipelago and includes all species of the region from any published source (Branton,

2010a).

The Living Marine Legacy of Gwaii Haanas II lists all invertebrate species and their

distributions from the first records in 1880 to 2000 from the intertidal to the deep-sea,

containing 25 000 records of over 2 500 species from 2 900 localities (Branton, 2010b).

The EAISSNA Electronic Atlas of Ichthyoplankton is a georeferenced database on the

distribution of fish eggs and larvae on the Nova Scotian Shelf. 197 scientific publications


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from 1919 to 2001 were reviewed providing information on 107 taxa of fish and

invertebrates. The information and is useful for environmental managers, oil industry and

fisheries researchers (Branton, 2010c).

The Eastern Canadian Benthic Macrofauna database is to map biomass and productivity of

benthic communities on the continental shelf to support ecosystems research in eastern

North America. Biomass measurements from 1954 to 2000 were georeferenced in the

database (Branton, 2009).

16.9.11 Coastal Defence & Military Activities

16.9.12 Ports & Maritime Navigation

16.9.13 Tides and Currents The Coastal Environmental Data - Northern and Eastern Canada database is necessary for

understanding coastal processes through measuring current, wave, water level and

meteorological data (Manson, 2010).

16.9.14 Wind and Waves

16.9.15 Bathymetry

16.9.16 Sea-Ice The purpose of the 1:10 000 000 North American Atlas for Sea-Ice is to be displayed and

used for the continental level analysis. Basic data layers enclose roads, railroads, populated

places, political boundaries, hydrography, bathymetry, sea ice and glaciers, which have all

been processed to be in correct positions relatively to each other. The data originated from

the Canadian Ice Service and shows the average minimum ice cover over a 30 years’ time in

1969-1999 (GeoGratis, 2011).

16.9.17 Chemistry The EMODNET Chemistry portal can be accessed at:

http://emodnet-chemistry.maris2.nl/v_cdi_v2/intro_cdi.asp

The colour indicates the number of measurement datasets. Clicking on a coloured square

selects a specific variable and marine region, whereby the results are presented. Pointing

the mouse on a coloured square displays the number of available datasets.

16.9.18 Baltic Sea This chapter is based on the MyOcean Catalogue (MyOcean, 2013). See also: http://www.myocean.eu/automne_modules_files/pmedia/public/r124_9_myocean_catalogue_v3.0_23_april_

2013_-_without_view.pdf

http://emodnet-chemistry.maris2.nl/v_cdi_v2/intro_cdi.asp

http://www.myocean.eu/automne_modules_files/pmedia/public/r124_9_myocean_catalogue_v3.0_23_april_2013_-_without_view.pdf

http://www.myocean.eu/automne_modules_files/pmedia/public/r124_9_myocean_catalogue_v3.0_23_april_2013_-_without_view.pdf


85

16.9.18.1 Sea Surface Temperature

Daily maps of sea surface temperature at 0.02degrees x 0.02degrees spatial resolution from

the following sensors: NOAA AVHRR, Metop AVHRR, Terra MODIS, Aqua MODIS, Aqua

AMSR-E, Envisat AATSR and MSG Seviri. Applications: Numerical weather and ocean models

and monitoring of the Baltic Sea.

16.9.18.2 Ocean Colour

The Ocean colour is based on the chlorophyll- in mg/m3 over Baltic Sea and at 1km

resolution. Data is merger from MERIS, MODIS/AQUA and SeaWiFS. For details, see:

Maritorena, S., O. Hembise Fanton d’Andon, A. Mangin & D.A. Siegel, 2010. Merged Ocean

Colour Data Products Using a Bio-Optical Model: Characteristics, Benefits and Issues.

Remote Sensing of Environment.

Fanton d'Andon O.H., D. Antoine, A. Mangin, S. Maritorena, D. Durand, Y. Pradhan, S.

Lavender, A. Morel, J. Demaria, G. Barrot (2008) Ocean colour sensors characterisation and

expected error estimates of ocean colour merged products from GlobColour, Ocean Optics,

Barga.

16.9.18.3 Daily Ocean Colour Optics

These products are merged from MERIS, MODIS/AQUA and SeaWiFS. Purpose: Education,

marine safety, environment, climate and seasonal studies. Please, refer to: GlobColour Full


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Validation Report at

http://www.enviport.org/globcolour/validation/report/GlobCOLOUR_FVR_v1.1.pdf.

16.9.18.4 Physical Analysis

The Baltic Sea physical model provides forecasts for the

physical conditions in the Baltic Sea. The product is provided on a grid with horizontal

resolution of 1 nautical mile and in 25 vertical depth levels. Data are available online for the

latest 3 months.

16.9.18.5 Mean Ocean Topography

For the Global Ocean- Mean Dynamic Topography computed on a 7 years period (1993-

1999). More information: Rio, M.-H., Schaeffer, P., Lemoine, J.-M., Hernandez, F.,

Estimation of the ocean Mean Dynamic Topography through the combination of altimetric

data, in-situ measurements and GRACE geoid: From global to regional studies, Proceedings

of the GOCINA international workshop, Luxembourg, 2005.

16.9.18.6 Sea-Ice Concentration and Thickness

Ice thickness chart (ITC), ice drift and ice concentration are derived from Envisat ASAR and

RADARSAT-2, in a 0.1-1km grid. J. Karvonen, M. Similä, SAR-Based Estimation of the Baltic

Sea Ice Motion, Proc. of the International Geoscience and Remote Sensing Symposium 2007

(IGARSS 07), pp. 2605-2608, 2007.

16.9.18.7 Sea Surface Height

The European Ocean (North-West Shelf, Iberic-Biscayan-Ireland Mediterranean Sea, Black

Sea and Baltic Sea): Mono altimeter satellite along-track sea surface heights computed with

respect to a seven-year mean.

http://www.enviport.org/globcolour/validation/report/GlobCOLOUR_FVR_v1.1.pdf


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16.9.18.8 Bio-Geo-Chemistry Analysis

The Baltic Sea biogeochemical product on a grid of 1 nautical mile spatial resolution, and in

25 vertical depth levels. See: Neumann, 2000. Towards a 3d-ecosystem model of the Baltic

Sea. J. Mar. Syst. 25, 405-419.

16.9.18.9 Physics Re-Analysis

Monthly mean fields for the physical conditions in the Baltic Sea based on 20 year reanalysis

simulations for the period January 1990 - December 2009

16.9.18.10 In-Situ near Real-Time Observations

The In Situ Thematic Assembly Centre (INS TAC) collects near real-time in-situ observation

data. These data are collected from the BOOS members. Variables:

- Mass concentration of chlorophyll a

- Moles of oxygen per unit mass

- Sea surface height

- Salinity

- Temperature

- X velocity

- Y velocity

Ocean circulation models need information on the interior of the ocean only available from

in-situ measurements.


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16.9.18.11 Ocean Wind Observations

Daily gridded sea surface wind observations from the ASCAT scatterometers on board

METOP-A and METOP-B. Resolution: 0.125 or 0.25. IFREMER CERSAT surface wind

climatology Fields for the Global Ocean include wind components, wind module and wind

stress available since April 2007.

16.9.18.12 Baltic Operational Oceanographic System

BOOS aims at integrating marine services to users and policy makers with objectives to

improve the maritime safety, sustainable use of Baltic Sea resources, offshore energy

activities, environmental hazards and pollution avoidance, ocean climate studies, and

federate resources of diverse institutes: http://www.boos.org/

http://www.boos.org/


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16.10 Marine Geospatial Portals This chapter provides a random list of some marine geospatial portals. There are very many

others, because most of the maritime countries are providing their own native services. In

addition, there are several other international portals not mentioned here for a reason.

16.10.1 Copernicus (former GMES) The European Copernicus Marine Monitoring service provides regular information on

temperature, salinity, currents, wind, sea level and sea-ice. The observation infrastructure

consists of several Remote Sensing satellites and in-situ components. In addition, to Marine

Monitoring, Copernicus services cover Land Monitoring, Atmospheric Monitoring,

Emergency Management, Security and Climate Change. There is a very large number (about)

of EU research projects, which can be searched and accessed through the Copernicus

Database of projects. Source: http://copernicus.eu/pages-principales/services/marine-monitoring/

16.10.2 GEBCO Ocean Mapping The General Bathymetric Chart of the Oceans (GEBCO) comprises 18 separate bathymetric

map sheets covering all oceanic areas. The GEBCO chart is produced together with the

UNESCO Intergovernmental Oceanographic Commission (IOC) and IHO. GEBCO can be

accessed through their web page at http://www.gebco.net/.

16.10.3 NOAA Digital Coast The NOAA Coastal Services Center is listing 891 layers of data in 12 themes for all the states

of USA. In addition to data, they also have tools, training and case studies available. The

service is accessible in here: http://www.csc.noaa.gov/digitalcoast/.

16.10.4 US Integrated Ocean Observing System (IOOS) IOOS has currently 2524 observation platforms around the coastal USA. The observing

systems include underwater gliders, coastal radars and animal telemetry. They are

addressing the following information need themes: marine operations (e.g. SAR), coastal

hazards, climate variability, and ecosystems, fisheries and water quality. “Today, U.S. IOOS

has a mandate to "lead the integration of ocean, coastal, and Great Lakes observing

capabilities.” Source: http://www.ioos.noaa.gov/

16.10.5 Seafloor Mapping Lab Data Library SFML data include multi-beam and side scan sonar imagery together with bathymetric

contours, grid analyses, habitat analyses, coastline and other associated datasets with FGDC

metadata. Survey locations are shown on the map in Figure 28. Clicking a square survey

location at the web site (http://seafloor.otterlabs.org/SFMLwebDATA_SURVEYMAP.htm) will open a

menu similar to that shown on the right in Figure 28, where the actual data can be very

easily downloaded and freely used. The multi-beam and side-scan sonar images are in

GeoTIFF format and other data in ArcGIS shape files or in ArcGIS grids (SFML, 2013).

http://copernicus.eu/pages-principales/services/marine-monitoring/

http://www.gebco.net/

http://www.csc.noaa.gov/digitalcoast/

http://www.ioos.noaa.gov/

http://seafloor.otterlabs.org/SFMLwebDATA_SURVEYMAP.htm


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Figure 28. SFML data locator map (left) and download menu (right) (SFML, 2013).


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16.10.6 GeoConnections “The Canadian GeoConnections Discovery Portal is a metadata catalogue that enables GIS

users, developers and data suppliers to find, evaluate, access, visualize and publish Canadian

geospatial and geoscience data products and Web services” (GeoConnections, 2013).

There are 17 topic categories in the GeoConnections Discovery Portal and the number of

databases under each category is shown in Table 8. The databases were further searched by

us using the keywords “ocean”, “marine”, “sea” and “maritime” in order to find out the

number of databases in each category.

And, it was found out that there were 7311 (38%) databases mentioning the word “ocean”,

1269 (6.6%) mentioning “sea”, 434 (2.3%) mentioning “marine”, 343 (1.8%) mentioning

“coast” and 72 mentioning “maritime”. These percentages are shown on the last row of

Table 8. The lowest occurrence of these words was in the following categories:

Atmosphere and Climate, where 52 (5.5%) of the 939 databases mentioned “ocean”

Biology and Ecology, where 57 (5.7%) of 1007 mentioned “ocean”

Environment and Conservation, where 54 (4.5%) of 1204 mentioned “ocean”

Public Health and Disease, where 1 of 15 mentioned “coast”, but none of the other

Table 8. Topic categories of the Canadian GeoConnections Discovery Portal.

Category Number of Databases

Ocean %

Sea %

Marine %

Maritime %

Coast %

Administrative and Political 1688 56.6 9.2 0.8 0.1 0.5

Agriculture and Farming 554 48.7 4.0 2.3 0.7 2.3

Atmosphere and Climate 939 5.5 5.3 2.9 0.2 1.5

Biology and Ecology 1007 5.7 7.0 2.7 0.8 3.9

Business and Economic 1366 25.8 0.3 1.6 0.1 0.4

Cadastral 648 46.9 0.3 0.6 0.3 0.2

Cultural, Society and Demographic 1750 20.1 0.0 1.1 0.2 0.1

Elevation and Derived Products 320 85.3 2.5 4.7 1.6 4.1

Environment and Conservation 1204 4.5 4.7 2.6 0.8 2.2

Geological and Geophysical 392 38.0 18.9 13.5 1.0 13.3

Imagery and Base Maps 1157 50.7 14 2.3 0.8 2.9

Inland Water Resources 1419 47.7 4.2 1.8 0.4 2.5

Locations and Geodetic Networks 1790 36.1 0.0 0.9 0.1 0.2

Oceans and Coasts 1995 55.0 30.1 5.3 0.5 4.4

Public Health and Disease 15 0.0 0.0 0.0 0.0 6.7

Public Safety and Security 13 38.5 23.1 15.4 0.0 30.8

Transportation Networks 1968 39.4 0.1 1.2 0.2 0.2

Utilities and Communication 991 71.0 0.1 0.9 0.2 0.2

Total 19216 38.0 6.6 2.3 0.4 1.8

The total number of databases on the GeoConnections Discovery Portal was 19216 and the

portal opens in the following web address http://geodiscover.cgdi.ca.

http://geodiscover.cgdi.ca/


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16.10.7 MyOcean The 7 MyOcean geographical areas include: Global Ocean, Arctic Ocean, Baltic Sea, Atlantic

European North West Shelf Ocean, Atlantic Iberian Biscay Irish Ocean, Mediterranean Sea

and Black Sea. And, the products contain the following parameters: ocean temperature,

ocean salinity, ocean currents, sea-ice, sea-level, winds, ocean optics, ocean chemistry,

ocean biology, ocean chlorophyll. There are 107 products available in the catalogue at

http://www.myocean.eu/.

MyOcean data can be downloaded regularly and automatically by choosing the SUBSET or

the DIRECT download mechanism using a Python script. The data format is Network

Common Data Form (netCDF), which is a set of software libraries and machine-independent

data formats. This is also a community standard for sharing scientific data. A netCDF file

both metadata and data. netCDF programming interfaces are available for C, Java, Fortran,

C++, IDL, MATLAB, Perl, Python, R and Ruby (Unidata, 2013). Some useful netCDF tools

include (See also http://ww.unidata.ucar.edu/software/netcdf):

Decompressors

o WinZip, http://ww.winzip.com

o Bzip2, http://ww.7-zip.org, http://ww.bzip.org

Visualisation tools

o Ncview, http://meteora.ucsd.edu/~pierce/ncview_home_page.html

o Ferret, http://ferret.wrc.noaa.gov/Ferret

o Matplotlib Python library, http://matplotlib.sourceforge.net

o Ncl, http://www.ncl.ucar.edu

o Idv, http://www.unidata.ucar.edu/software/idv (advanced view with 3D animation)

Manipulation tools

o NetCDF software with Fortran, C++ etc. libraries is freely available at

http://www.unidata.ucar.edu/software/netcdf/docs/faq.html#howtoget being the

best tool for processing NetCDF files, enclosing file format conversions.

o The NetCDF Operators (NCO) is a powerful set of tools for extraction,

concatenation or adding attributes: http://nco.sourceforge.net

o Marine Geospatial Ecology Tools at http://code.env.duke.edu/projects/mget is

also an addition to ArcGIS for NetCDF format conversions to ASCI or ArcGrid.

Converting tools from NetCDF to GRIB e.g.

o Ncl: http://www.ncl.ucar.edu

16.10.8 IHO Bathymetry Although 70 % of the Earth surface is covered by ocean, the world´s oceans remain poorly

mapped. Yet only about 10% of the seafloor has been surveyed by echo sounders at a

resolution of around 1 minute or better (IHO, 2013). This is very much in contrast to dry

land, where satellite instruments, like the ENVISAT MERIS or LANDSAT ETM, have ( at least

in theory) been able to acquire imagery with global coverage (i.e., where the cloud-cover is

not hindering the visibility) at resolutions of 1km every 3 days, or 30m every 16 days,

correspondingly. Even much higher resolution imagery (as fine as 50cm resolution from

satellite and near-cm-resolutions from the airplane) is readily available anywhere over the

http://www.myocean.eu/

http://ww.unidata.ucar.edu/software/netcdf

http://ww.winzip.com/

http://ww.7-zip.org/

http://ww.bzip.org/

http://meteora.ucsd.edu/~pierce/ncview_home_page.html

http://ferret.wrc.noaa.gov/Ferret

http://matplotlib.sourceforge.net/

http://www.ncl.ucar.edu/

http://www.unidata.ucar.edu/software/idv

http://www.unidata.ucar.edu/software/netcdf/docs/faq.html#howtoget

http://nco.sourceforge.net/

http://code.env.duke.edu/projects/mget

http://www.ncl.ucar.edu/


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populated land (immediately visible in Google Earth or Bing Maps, for example) or a new

acquisition can be arranged on request by a satellites in weeks with prices not much higher

than 1000 US dollars per 100 km2.

Bathymetric data is important as well for navigation through nautical charts as for Earth

sciences. Knowing, the shape of the ocean basins, ridges and mountains, the flow of sea

water carrying nutrients, pollutants, heat and salt can be modelled. Undersea seismic events

can also be analysed. The IHO Data Centre for Digital Bathymetry (DCDB) collects oceanic

soundings from vessels. Shallow water soundings have been derived from national products

such as Electronic Nautical Charts (ENC).

16.10.9 SeaDataNet “SeaDataNet is a pan-European infrastructure providing harmonised discovery services and

access to ocean and marine environmental data sets managed in distributed data centres.

The partnership is composed of 44 institutions directly involved in the project as partner and

10 other institutions as associate partner, from 35 countries riparian to European seas”

(SeaDataNet, 2013b).

SeaDataNet comprises following services, as depicted in Figure 29 (SeaDataNet, 2013c):

Discovery services = Metadata directories

Viewing services = Visualisation of metadata, data and data products

Delivery services = Data access & downloading of datasets

Product services = Generic and standard products

Security services = Authentication, Authorization & Accounting (AAA)

Monitoring services = Statistics on usage and performance of the system

Maintenance services = Updating of metadata by SeaDataNet partners


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Figure 29. SeaDataNet user’s portal systems architecture (SeaDataNet, 2013).

The aim of SeaDataNet is to provide an integrated access to data, managed by distributed

data centres. Moreover it provides users the following common data analysis tools:

- MIKADO java tool - Editing and generating XML metadata

- EndsAndBends - Generation of spatial objects from vessel navigation

- Med2MedSDN - Conversion of the Medatlas format to SeaDataNet

- NEMO java tool - Conversion of any ASCII format to the SeaDataNet

- Download Manager - Connecting Data Centres to the SeaDataNet portal

Ocean Data View (ODV) Analysing and visualising

- DIVA - Interpolation and variation analysis

The SeaDataNet infrastructure links 80 national oceanographic data centres and marine

data centres from 35 countries riparian to all European seas. The data centres manage large

sets of marine and ocean data, originating from their own institutes and from other parties

in their country, in a variety of data management systems and configurations. A major

objective and challenge in SeaDataNet is to provide an integrated and harmonised overview

and access to these data resources, using a distributed network approach.

This is achieved by developing and implementing the Common Data Index service, which

gives users a highly detailed insight in the availability and geographical spreading of marine


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data across the different data centres across Europe. The CDI provides an ISO19115 based

index (metadatabase) to individual data sets (such as samples, time series, profiles,

trajectories, etc.) and it provides a unique interface to online data access. Data sets are

available in ODV format which can be used directly in the Ocean Data View (ODV) software

package including the Data Interpolating Variation Analysis software tool (DIVA).

16.10.10 Global Ocean Observing System (GOOS) The Global Ocean Observing System (GOOS) is a permanent ocean observation, modelling

and analysis system of marine variables including state of the oceans, living resources and

climate change forecasts. The GOOS is the oceanographic component of the Global Earth

Observation System of Systems (GEOSS ) and it is supported by UN and UNESCO. GOOS aims

at understanding weather and climate, state of the ocean, marine life, improve marine

management, mitigate natural hazards and pollution, protect life and property at the sea,

and enable scientific research (GOOS, 2013). GOOS is collecting data from a multitude of

sources, including near real-time satellite and buoy observations on water and air

temperature, air pressure, air humidity, ocean currents, water salinity, sea-level, sea-ice,

plankton, wave characteristics, coral reefs, voluntary ship observations, biodiversity,

tsunami etc. A complete list with access to these and other data is available at the following

web site: http://gosic.org/goos. Currently, there are 108 programmes related to GOOS: http://www.ioc-goos.org/index.php?option=com_content&view=category&id=36&layout=blog&Itemid=131&lang=en.

16.10.11 Geo-Seas In Geo-Seas there are 26 marine geological and geophysical data centers from 17 European

maritime countries. A major objective and challenge in Geo-Seas is to provide an integrated

and harmonized overview and access to these data resources using the CDI service through

an ISO19115-based index (metadatabase) to individual data sets (such as samples, time

series, profiles, trajectories, etc. All the 26 Geo-Seas data centers are fully operational

delivering data directly through discovery and access services. As a result there are now in

excess 130,000 metadata records. The aims of Geo-Seas are aligned with European

directives and recent large-scale framework programmes on global and European scales,

such as GEOSS and GMES, EMODNET and INSPIRE (Geo-Seas Web page, 2013).

16.10.12 Pan-European Metadata Services This chapter is based on an overview of Pan-European marine research organisations as given at the SeaDataNet internet page and the user-interface are presented in

Figure 34 and

Figure 35 on page 131 and 101, correspondingly. All the services listed below can be

accessed through this web address: http://www.seadatanet.org/Metadata.

http://gosic.org/goos

http://www.ioc-goos.org/index.php?option=com_content&view=category&id=36&layout=blog&Itemid=131&lang=en


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16.10.12.1 European Directory of Marine Organisations (EDMO)

EDMO contains addresses and activity profiles of research institutes, data holding centres,

monitoring agencies, governmental and private organisations engaged in marine research,

data management or data acquisition. More than 1500 organisations are listed. See above.

16.10.12.2 Directory of Marine Environmental Data (EDMED)

EDMED is a reference to marine datasets of over 700 European research laboratories or

data centres, covering disciplines such as marine meteorology, physical, chemical and

biological oceanography, sedimentology, biology, fisheries, environment, coast, and marine

geology. There are more than 3500 datasets across the Europe. The Web address is above.

16.10.12.3 Directory of Marine Environmental Research (EDMERP)

EDMERP covers over 1800 marine research projects across Europe with subjects as above.

16.10.12.4 Cruise Summary Reports (CSR)

Cruise Summary Reports directory covers cruises from year 1873 till today of more than

2000 research vessels and nearly 40000 cruises, in global oceans and all European waters.

16.10.12.5 Directory of the initial Ocean-observing Systems (EDIOS)

EDIOS is an initiative of EuroGOOS listing ocean measuring systems in Europe, as compiled

from national contributions. As always in the chapter, the web address is given above.

16.10.12.6 Nordic Open Source Initiative Network

GeoNetwork was selected as a starting point for Nordic Geo-Portals project originally in

Denmark, Norway, Finland, Sweden and Scotland and it was developed together further in

order to fulfil the requirements of the INSPIRE directive. Prioritised list of requested

functionality was created (Lindegaard, 2011). Lindegaard reminded of the cooperation that

custom-build solutions are difficult to replace. See:

http://geonetwork-opensource.org/

http://www.geodata-info.dk/Portal/

http://www.geodata.se/

http://www.geodata.no/

http://www.paikkatietoikkuna.fi/web/en

http://geonetwork-opensource.org/

http://www.geodata-info.dk/Portal/

http://www.geodata.se/

http://www.geodata.no/

http://www.paikkatietoikkuna.fi/web/en


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16.10.12.7 PRIMAR

Figure 30. PRIMAR worldwide ENC coverage (on the left) in Finland (PIMAR, 2013).

Figure 31. PRIMAR ENC search result from Nauvo (on the right), Finland (PIMAR, 2013).

Figure 32. PRIMAR worldwide ENC coverage around England (PIMAR, 2013).

Source: https://www.primar.org/web/10180/15

16.10.13 UK National Oceanographic Database (NODB) This index provides access to all data series held in our National Oceanographic Database

(NODB), a collection of marine data sets maintained by BODC, originating from a wide range

of organisations. Parameter categories include, for example

https://www.primar.org/web/10180/15


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- Acoustics

- Bathymetry and topography

- Currents - horizontal and vertical velocity, Lagrangian currents and water transport

rates Meteorology - Radiosonde, Meteorological stations and data buoys

- Optical properties - pigments, turbidity, irradiance

- Sea level

- Water column temperature and salinity

- Water column chemistry - nutrients, carbons, oxygen

- Waves - statistics and spectra

The NODB index includes 88129 data series from 148 different organisations.

Source: https://www.primar.org/web/10180/15

16.10.14 Finland Paikkatietoikkuna (www.paikkatietoikkuna.fi) is the finnish SDI. Unfortunately, an MSDI is

not available probably due major organisational changes of breaking down the Finnish

Maritime Administration in to private companies in 2010 and the Finnish Maritime Research

Center between the Finnish Environment Institute and Meteorologial Instutute a few year

earlier. The governmental Traffic Agency has however promised that marine products will

be opened ”little by little” (Traffic Agency web page, 2013). The SDI has in any case been a

success, with over 40,000,000 service requests monthly in 2012 .

Other Finnish portals of spatial information include:

Kansalaisen Karttapaikka www.kansalaisen.karttapaikka.fi

Tampereen kaupunki

PaikkaOppi www.paikkaoppi.fi

Palvelukartta www.suomi.fi/suomifi/suomi/palvelukartta

Museovirasto

Vipu-palvelu www.mavi.fi/fi/index/viljelijatuet/vipu.html

Työ- ja elinkeinoministeriö www.mol.fi, www.eharava.fi, www.lupapiste.fi

Reittiopas www.reittiopas.fi

Pääkaupunkiseudun Palvelukartta www.hel.fi/palvelukartta

https://www.primar.org/web/10180/15

http://www.paikkatietoikkuna.fi/

http://www.kansalaisen.karttapaikka.fi/

http://www.paikkaoppi.fi/

http://www.suomi.fi/suomifi/suomi/palvelukartta

http://www.mavi.fi/fi/index/viljelijatuet/vipu.html

http://www.mol.fi/

http://www.eharava.fi/

http://www.lupapiste.fi/

http://www.reittiopas.fi/

http://www.hel.fi/palvelukartta


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Figure 33. The most important waterways of Finland (Liikennevirasto, 2013).


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Figure 34. Pan-European marine metadata services (SeaDataNet, 2013).


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Figure 35. SeaDataNet direct access to data (SeaDataNet, 2013).


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Figure 36. Arc Marine thematic layers (Wright et al., 2007). Cont. …


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Figure 37. … Cont. Arc Marine thematic layers (Wright et al., 2007).


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Figure 38. Ship track lines from 1980-2010 hydrographic surveys (GEBCO, 2011).


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Figure 39. Sea depth contours, lakes, rivers and swamps of South-East Finland highlighted.


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Figure 40. CleanTOPO2 - 3D version rendered as an oblique view (Patterson, 2013).


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Figure 41. Gravity from satellite altimetry, version 15, Sandwell & Smith, 2006.

“Imagine taking one depth measurement every couple of kilometres” (GEBCO, 2011).

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