Aplikasi Teknologi Multimedia dalam Manajemen Layanan Basis Data dan Teknologi Informasi

UJIAN KOMPETENSI DASAR 1

SEMESTER GENAP TAHUN AKADEMIK 2014/2015

Mata Kuliah/SKS : Teknik Multimedia / 3

Dosen Penguji : Meiyanto Eko Sulistyo, S.T., M.Eng.

Soal Ujian Kompetensi Dasar 1 Teknik Multimedia :

1. Mencari 1 topik jurnal berbahasa inggris yang berkaitan dengan Representasi Media dan Format

Media dicetak di kertas ukuran kuarto (A4) !

2. Buatlah resume dari soal nomor 1 dan dicetak di kertas ukuran kuarto (A4) !

3. Hasil tugas soal nomor 1 dan 2 dikumpulkan pada hari Jumat 6 Maret 2015 jam 10:00 WIB di

meja kerja Pak Meiyanto Eko Sulistyo dengan menandatangani Presensi Kuliah Sesi Ke-4 (Kolom

Ke-4) Teknik Multimedia dan Presensi Ujian Kompetensi Dasar 1 (Kolom Ke-1) Teknik

Multimedia !

4. Tugas Ujian Kompetensi Dasar 1 Teknik Multimedia ini bersifat mandiri dan tidak boleh sama !

UNIVERSITAS SEBELAS MARET

FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM

JURUSAN INFORMATIKA

International Journal of Computer Applications (0975 – 8887)

Volume 103 – No.7, October 2014

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Application of Multimedia Technology in Database and

IT Service Management

Onimode Bayo Mohammed

Computer Science Department Federal University of Technology, Minna

Niger State, Nigeria

ABSTRACT

Multimedia is a blend of two or more media such as text,

sound, graphics, animation and video, to effectually converse

ideas to the users and this could be in linear or non-linear

form [7]. The application of multimedia technology to

database and IT service management has improved

enormously in recent times. Multimedia system is a

distinctive application which is of time-critical in its use in the

various areas of computing. The spatial, secular, storage,

processing, recovery, grouping and management requirements

of data vary momentously from those that are applied for

traditional data [2]. Therefore, the purpose of multimedia

technology in database management system and in proper

management of IT services to clients is to permit for an

efficient way of performing these tasks in all its varied forms

in an efficient form. A multimedia database management

system affords an efficient storage and manoeuvring of

multimedia technologies in all its diverse types. Database

technology has offered means to store and recover high

volumes of data in the various business domains [8].

Although, database systems have always been planned for the

administration of alphanumeric data such as names and

numbers, the basic nature of multimedia data are also

considered and thus highlights the need for multimedia

enhanced database management systems, and present the

various obligations and issues required for developing such

systems. The various areas of applications consist of, but not

limited to digital libraries (text documents, images, sound,

video etc), art and entertainment, content management,

journalism etc [1]. For technology purposes, multimedia is a

computer-based systems that apply associative relationships to

allow the users of such systems to navigate and retrieve

various information that are stored in a location which could

be a combination of text, sounds, graphics, video, and other

media formats [12].

Keywords

Multimedia, Technology, Database systems, metadata,

management, IT service management, Object-oriented.

1. INTRODUCTION

Multimedia database management system is at the heart of

multimedia information systems. Conventionally, a database

consists of a managed collection of related data that are

related to a given entity, whereas a database management

system, or DBMS, is a collection of data that are interrelated

with the set of programs that are applied to classify, produce,

store, access, run, and possibly query the database for use.

Equally, multimedia enhanced database can be viewed as a

organized collection of multimedia data items, such as text,

images, audio, graphic items, video and sketches [3]. Thus a

multimedia DBMS provides support for several multimedia

data types, and in addition services for the creation, access,

query, storage and control of the multimedia database. The

diverse data types that are involved in multimedia databases

may necessitate unique techniques for the optimal access,

indexing, storage and retrieval [5]. The multimedia DBMS

ought to contain these unique requirements by offering high-

level ideas to handle the different data types, along with a

suitable interface for their management. The composition and

character of multimedia data from the various perspectives is

also looked into [11]. These perspectives includes: excess

information, spatial and sequential characteristics, shortage of

textual depictions, array of data types, and the massive

volumes of data that are applied. The combination of

multimedia data types from unique but several sources

exclusively characterizes multimedia information systems.

Prior to detailing the abilities that are expected of a

multimedia DBMS and the obligations that such systems

should meet, consideration is first given to the attributes and

the nature of multimedia information we enhances it usage

and applications. Also application of multimedia technologies

in the management of IT services is also discussed [6].

Fig.1: A high level architecture for a multimedia DBMS

that meets the requirement for multimedia data.

2. MULTIMEDIA DATABASES

2.1 Multimedia Data: There exist a couple of data types that can be described as

multimedia data types. These are classic elements that are

applies as the building mass of the hub generalized

multimedia platforms, environments, or the integrating tools

used. Thus the basic data types found in a typical multimedia

database includes [1]:



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a) Text: the form in which the text can be stored can vary

greatly;

b) Audio: is generated from an auditory recording device;

c) Images: black and white, coloured, maps, photographs,

and paintings;

d) Graphic objects: ordinary drawings, sketches, and

illustrations, or 3D objects;

e) Animation sequences: images or graphic objects which

are usually independently generated;

f) Video: are also strings of images, called frames, but are

typically recording a real-life event and are usually

produced by a video recorder; and

g) Composite multimedia: is formed from a combination

of two or more of the above data types, such as an blend

of audio and video with a textual explanation.

Various multimedia data types like audio, video, and

animation sequences also have chronological requirements,

which have inferences on their storage, management, as well

as their presentation. The exertions become more heightened

when various data types from perhaps unrelated sources must

be offered within or at a given time. Likewise, graphics,

images, and video data have spatial limits in terms of their

content [14]. Usually, individual objects in an image or a

video frame have some spatial correlation between them.

Such correlations typically produce some limits when

searching for objects in a database. Large volumes of data

also characterize multimedia information. For example, to

store an uncompressed image of 1024 x 728 pixels at 24 bits

per pixel involves a storage capacity of about 2mb. With a

compression ratio of 20:1, the storage requisite could be

condensed to about 0.1mb. Thus considering an instance for

video, a 10-minute sequence of the same image at 30frames

per second needs about 38,000mb of storage, which can be

condensed to about 380mb using a compression ratio of 100:1

[6].

Fig. 2: A hierarchically storage for multimedia database

The potential for large volumes of data involved in

multimedia information systems becomes obvious when

considering for example, that a motion picture could run as

long as two hours, and classic video ordnance would

accommodate thousands of movies. An old adage says that a

picture is worth more than a thousand words [1]. However,

representing multimedia information as pictures or image

series poses some hitches for information recovery due to the

restraints of textual depictions of a multimedia practice and

the enormous information accessible from it. The prospective

information excess means that users may find it hard to make

exact demands during information recovery. The inadequacies

of textual narratives also imply the necessity for content-based

access to multimedia information. Users need multiple nods

(such as colour, shape, and texture) that are relevant to the

multimedia content [13]

An additional attribute of multimedia information is that of it

interface with such information types usually involves long-

period functions (such as with video data), with bits of more

than a single client (as is typical in joint support settings).

Conversely, in concerted settings, it is likely that the majority

of multimedia data are likely to be accessed in a read only

form. This assumption can be used to facilitate the provision

of concurrency control algorithms.

2.2 How Multimedia Technology is

differently applied in Database

Theoretically it ought to be feasible to treat multimedia

database in the equal manner as data that based on the data

types (for example: dates, numbers and characters),

nevertheless, there exist some challenges that occurs as a

result multimedia data as described in [17], these challenges

are:

a. In case of audio and video databases, the time to retrieve

information may be very crucial for example, video on

order.

b. Multimedia data is large and thus affects the storage,

processing, retrieval and transmission of multimedia

data as contained in the database.

c. The substance of multimedia data are frequently

captured with diverse “capture” procedures (for

example, image processing) that may be rather

unreliable. Multimedia processing techniques need to be

able to handle diverse ways of content capture including

manual ways and or automated methods.

d. Queries created by the user in the multimedia databases

repeatedly cannot return with a textual answer. Slightly,

the responses to a query may be a complex multimedia

presentation that the user can look through at his/her

spare time. Thus various outlines show how queries to

multimedia databases may be utilised to create

multimedia presentations that meet user’s queries [1].

e. In conventional databases, user explicitly submits the

point values of the objects inserted into the database;

this is an automatic feature extraction and Indexing

mode.

f. Comparatively, utilizing advanced tools such as image

processing and pattern recognition tools for images, to

extract the various elements and content of multimedia

objects. As the size of data becomes very large, there is

need for special data structures to be used for storing

and indexing of such data.

2.3 Basic Approaches for Data Retrieval

Database management has a much stretched history and lots

of approaches have been created to manage and query diverse

database types in the database management systems. As given

in [10], the fundamental approaches being applied for

database management can be categorized into the following

types:



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The conventional database system: This is the

broadly-used method to manage and search through a

database for structured data. All the data in a database

system thus must obey the rules of some predefined

structures and checks (that is, the schemas). To prepare

a database query, the user of such database must give

which data objects are to be retrieved, the database

tables from which they are to be extracted and predicate

on which the retrieval is based. A query language for the

database will generally be of the artificial kind, one with

controlled syntax and vocabulary, such as the SQL.

The Information Retrieval (IR) system: the IR system

is majorly used to search large text collections in a

database, in which the text of the data is described by an

indexer using keywords or a textual abstract, and

keywords or natural language is used to express query

demands. For example for an image or video we have to

describe it in words or in a way need to store lot of

metadata in textual form [4].

The Content Based Retrieval (CBR) system: This

approach is used to retrieve desired multimedia objects

from a large group on the basis of the features (such as

texture, shape, colour and, etc.) of the database that can

be automatically extracted from the objects themselves.

Although keyword can be treated as a ”feature” for text

data, traditional information retrieval has much more

higher performance than content-based retrieval because

keyword has the proven ability to represent semantics,

while no features have shown convincing semantic

describing ability. But major drawback of this method is

that it lacks precision.

The Graph or tree pattern matching: This approach

aims to retrieve object sub-graphs from an object graph

according to some denoted patterns specified.

2.4 Metadata

Metadata are data about data. The term “meta” comes from a

Greek word, denoting something of a higher or more

fundamental nature. Generally speaking, metadata can refer to

any data that are used to describe the content, condition,

quality, and other aspects of data for humans or machines to

be able to locate, access and understand the data contained.

Thus, metadata information can help the users to get a

synopsis of the data [3].

Why do we need Metadata?

When an image tells nothing about itself except the plain fact

that it is a picture of an object, without reading the associated

metadata, it is not possible for a user to discern the properties

of the image such as who snapped the picture, when and

where it was taken, what is the resolution of the picture

amongst others, all of which are very vital information that

helps to determine the appropriateness of the image for a

certain application before the user takes a look at the actual

data. Metadata thus plays far more significant role in the

management of multimedia data than does the running of

traditional well-structured data. Some of the reasons as

described by [9] include:

Different Query Paradigm: The exact-match idea for

querying is no longer apt or sufficient for querying or

retrieving various types of digital data.

Inadequate Processing Technique: Content-based

processing techniques are excessively hard to analyze

and very large data-sets are often limited or insufficient.

Lacking efficiency: When a content-based search is

possible, it can’t be used very regularly (for example,

for every query) due to routine rationales and because of

divergent application.

Semantics of multimedia data: Derive and Interpreted

data, which may be considered as a part of metadata; as

well as context and semantics (which may be easier to

base on metadata rather than on raw data) are of larger

value when working with multimedia data (especially

audio-visual data).

Metadata Classification

The classification of metadata to get very suitable concepts

aids in exploring metadata. Thus, metadata can be classified

based on [1]:

a) Dependence on content classification

Content-independent metadata: This type details

information that does not depend on the content of the

document with which it is associated with. Examples

of this type are location, the type-of-sensor used to

record it and modification-date of document. There is

no information content captured by these metadata but

they are still useful for retrieval of documents from

their actual physical location.

Content-dependent metadata: This type depends on

the content of the document it is associated with.

Examples of content dependent metadata are max-

colours, size of a document, number of rows and

columns in an image. Content-dependent metadata can

be sub-divided further into: –

Direct content-based metadata: This type is

based directly on the contents of a document. A

popular example of this is full-text indices based

on the text of the documents. Inverted tree and

document [Christos Faloutsos] vectors are

examples of this type of metadata.

Content descriptive metadata: This type

illustrates the content of document without direct

utilization of those contents. It often involves the

use of knowledge or human perception/cognition.

An example of this is the textual annotation that

describes the contents of an image. This type

come in two flavours:

1) Domain-independent metadata: these

metadata capture information present in the

document which is independent of the

application or subject domain of information.

Examples of these are the C/C++ parse trees

and HTML document type definition.

2) Domain-specific metadata: this type metadata

is described in a manner specific to the

application or subject domain of information.

Examples of such metadata are land-cover

from GIS and population from Census

domain. In case of structural data, the database

schema is an example of such metadata.

Another example is domain specific

ontologies, terms from which may be used to

construct metadata specific to domain.

b) Hierarchical Based Classification

This is another type of classification of metadata that is

possible as proposed by Gilliland-Swetland (1998):

[18]. This classification includes:



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Descriptive: are metadata that are used to identify or

describe information resources.

Technical: are metadata that are related to how a

system functions or metadata behaves.

Administrative: are metadata that are used in

managing and administering information resources.

Preservation: are metadata that are related to the

preservation management of information resource.

Source of Metadata

Metadata can be extracted from various sources that are

available from the system. Thus, the four main categories [12]

of metadata sources are:

a) Document content analysis: an obvious source for

metadata about an object is the object itself. An object

based indexer generates metadata using the object

independent from some precise usage. Typical content

analyzers are keyword extractors, language analyzers for

text documents or pattern recognizers for images [1].

b) Composite documents structure: In a number of cases,

learning objects are parts of a whole but are stored

separately. In such a case, the metadata available for the

whole is an interesting source for metadata about a

component. Not only is the enclosing object a source, also

the sibling components can provide relevant metadata. For

example, one slide in a slide show often gives relevant

context about the content of the next slide. This could be

considered as a special case of document context, called

“aggregation related context”.

c) Document usage: the real use of objects can provide us

with more flexible and lively metadata than the sometimes

more “theoretical” values that are provided by other

metadata sources, or even by human indexers. Systems

that track and log the actual use of documents by learners

are therefore a priceless source. These logs for example

store the time spent reading a document or solving

exercises. This metadata source category could be

considered as a “usage context”, and as such as a special

case of document context analysis.

d) Document context analysis: when an object is used in a

specific context and data about that context are available,

we can rely on the context to obtain information about the

object itself. One single learning object typically canbe

deployed in several contexts which provide us with

metadata about it.

Generation of Metadata

In the case of structured databases, the standard is to use a

schema report and associated information, such as the

database statistics as metadata, while in the case of

unstructured textual data and information retrieval, metadata

is generally limited to indexes and textual descriptions of such

data. Metadata in such cases provides a suitable basis for

building the higher forms of information. Metadata is

commonly generated using three methods [9]:

a) Analyzing raw data: In several cases, media objects are

analyzed and metadata is created according to the focus of

analysis. This is also known as explicit metadata

generation.

b) Semi-automatic augmentation: media results in addition

to meta-information, which cannot be obtained from the

raw material as such. Examples are the diagnostic findings

of a doctor related to computer tomography image, which

are based on doctor’s experience and state of art in

medicine.

c) Processing with implicit metadata generation: metadata

can be generated implicitly when creating raw media data.

For example, the digital camera can implicitly deliver

time and date for picture and video taken. Comparably, an

SGML editor generates metadata according to document

type definition when the document is edited. Generating

the metadata can easily be a tiresome task, although using

automatic tools may help. The task is more daunting when

attempting to generate a vast volume of metadata, lacking

the knowledge of the data, its usage, its background facts,

as well as its accuracy, etc. Before generating the

metadata, it is necessary to review all the relevant

documentation about the data.

Metadata standards

Standards are an important mean to achieve common

representation designs and interoperability of a system, and

hence it can play a key role in exploiting metadata [19]. There

are very many activities that goes on area including:

The development of metadata taxonomy to help

structure the discourse on metadata.

The definition of generic functionality for tools for the

development and operation of metadata base.

The definition of a meta-model registry structure to

achieve mapping among different meta-model, and

The development of ontology related to metadata

attribute and the description of data elements and

domains in terms of the naming, typing, classification

and the semantics.

3. IT SERVICE MANAGEMENT AND

MULTIMEDIA TECHNOLOGIES

It is now widely established that the provision of services and

it acceptance should be administered by an agreement. This is

necessary in order to define the parameters of the service, for

the benefit of both the provider and the recipient of such

service. It must obviously cover many other issues, as well as

defining the service itself. Sadly, the creation of an

appropriate and focused Service Level Agreement (SLA)

which in itself is NOT a trivial task can be aided by

multimedia technologies. An SLA is a part of a service pact

where a service is formally defined. In practice, the term SLA

is sometimes applied to refer to the agreed delivery time (of

the service or performance). [22] For an example, an internet

service provider (isp) will commonly include SLAs within the

terms of their contracts with the customers to define the

various level(s) of the service that is being sold in plain

language terms. In this case, the Service Level Agreement

will typically have a technical meaning in terms of mean time

to repair or the mean time to recovery (MTTR), the mean time

between failures (MTBF) as well as the various data rates, the

throughput or any other similar measurable details.

IT System support

Efforts on various fronts have concentrated on the issue of

service management, including research on resource

scheduling, operating system support for Quality of Service

(QoS), the use of multilevel and user-level threads, etc. Other

characteristics of multimedia, such as the huge data volumes,

may mandate special constraints on the system in terms of the

memory management, CPU performance, throughput, and so

on. Allied issues include general considerations on input/

output (I/O) hardware to support the various media types



29

involved that are involved in multimedia databases.

Communication networks – that are required to convey the

data for distributed multimedia environments - must support

the bandwidth and delay guarantees as needed to meet the

stringent QoS requirements for certain multimedia

applications.

Applications

Broadly speaking, multimedia database management systems

applications can be established wherever there is a need to

manage multimedia data cost-effectively. Therefore

multimedia DBMSs have found applications in such varied

areas as healthcare (telemedicine, integrated health

information management, medical image systems), education

(digital libraries, training, presentation, distance learning),

entertainment (video-on-demand, music databases, interactive

TV), information dissemination (news-on-demand,

advertising, TV broadcasting), and manufacturing (distributed

manufacturing, distributed collaborative authoring). Such

other areas of its application may consist of finance, e-

commerce, electronic publishing, geographic information

systems, video conferencing, etc [20].

A number of multimedia DBMSs are already in existence.

Most of them are annexes from existing relational or object-

oriented DBMSs. The competence of existing multimedia

DBMSs can be appraised by the extent to which they can

support different media types (especially image and video).

They can also be evaluated by their ability to support special

functionalities required of a database system to manage

multimedia data, such as real-time delivery and content based

query and retrieval [15]. Regrettably, most existing

multimedia DBMSs fall short of this. Nonetheless, rigorous

research is variously being geared toward the various parts of

the problem and as such it is expected that new systems with

higher and better capabilities in the near future will emerge.

Future trends include performing indexing, retrieval, and

browsing directly on the compressed data, especially for video

data; video data management; multimedia query language;

uniform indexing frameworks for the different data types;

content-based image and video retrieval; and multimedia

transport and delivery over the Internet [12].

4. CONCLUSION

TheMultimedia data should be stored with advanced data

structures and with the aid of metadata in order to make it

search and retrieval process simpler. Thus an approach on

how images can be stored using data structures and can be

searched has been examined. This data structure helps to

remove attributes from data like image or video so that we can

execute content based queries. Also the advantage and

disadvantage of these data structures were discussed.

However, sometimes the indexing and searching process

consume lots of time in case of large databases [21]. So we

need help of metadata to make that process faster which does

not require extracting characteristics and information from the

data itself. Also presented is how metadata is generated and it

mentioned several issue that have to be undertaken. Also how

metadata can be classified so that depending upon the context,

better use of it can be made. Also how metadata standards can

assist exploiting use of metadata. In general, multimedia

applications and distributed multimedia database systems

especially, raise some new issues in all aspects of the

computer system, these ranges from operating systems to

networks to the general hardware [16]. Broadly available

operating systems do not support real-time operations

sufficiently. Somewhat, they offer hardware front-ends for

conveying and presenting multimedia data. Some multimedia

data, such as continuous media, may require real-time

delivery and presentation, while the real-time requisites might

not be as rigid as those encountered in hard real-time systems.

Therefore, the multimedia database system cannot fully

provide its functionalities until support for real-time

continuous media data becomes an integral part of the

operating system.

5. ACKNOWLEDGMENTS

I acknowledge the original and earlier works of Ajit Burad

(Multimedia Databases, Computer Science and Engineering,

Indian Institute of Technology, April 6, 2006, Donald A.

Adjeroh and Kingsley C. Nwosu (Multimedia Database

Management – Requirements and Issues) as well as Milko

Marinov and Dimitar Radev (An Implementation of a

Multimedia Object-Oriented Database Management System).

6. REFERENCES

[1] Ajit Burad, “Multimedia Databases”, Computer Science

and Engineering, Indian Institute of Technology, April 6,

2006

[2] Antonm Guttman, “R-trees: A dynamic index structure

for spatial database” Proceedings ACM SIGMOD

Conference, pp.47-57, Boston, MA, 1984.

[3] Arjen P. De Vries, “Content and Multimedia database

Management Systems” Centre for Telematics and

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[4] Christos Faloutsos, “Indexing Multimedia Database”

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California, May 22-25,

[5] Danail Dochev, Irena Koprinska and Radoslav Pavlov,

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[6] Donald A. Adjeroh, Kingsley C. Nwosu, Multimedia

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[12] Kris Cardinels, Michael Meire, Erik Duval, “Automating

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[16] Robert Garcia and Oscar Celma, “Semantic Integration

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IJCATM : www.ijcaonline.org

UJIAN KOMPETENSI DASAR 1

TEKNIK MULTIMEDIA

FEMBI REKRISNA GRANDEA PUTRA

M0513019

JURUSAN INFORMATIKA

FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM

UNIVERSITAS SEBELAS MARET

SURAKARTA

JUMAT, 6 MARET 2014

Aplikasi Teknologi Multimedia dalam Manajemen Layanan Basis Data

dan Teknologi Informasi

ABSTRAK

Multimedia adalah campuran dua atau lebih media seperti teks, suara, gambar, animasi, dan

vide yang secara efektif mengonversi ide pengguna dalam bentuk linear atau nonlinear.

Aplikasi dari teknologi multimedia dalam manajemen layanan basis data dan teknologi

informasi telah sangat berkembang dalam waktu ini. Sistem multimedia adalah sebuah aplikasi

tersendiri yang memiliki waktu-kritis dalam penggunaannya di setiap area komputasi yang

berbeda.

Kata Kunci

Multimedia, Teknologi, sistem Basis Data, metadata, manajemen, manajemen layanan

teknologi informasi, Berorientasi-objek.

1. INTRODUKSI

Sistem manajemen basis data multimedia adalah jantung dari sistem informas i

multimedia. Secara konvensional, sebuah basis data mengandung sebuah koleksi

teratur dari data yang berhubungan terhadap suatu entitas yang diberikan, di mana

sebuah sistem manajemen basis data, atau DBMS, adalah sebuah koleksi data yang tidak

saling terhubung dengan seperangkat program yang digunakan untuk

mengklasifikasikan, memproduksi, menyimpan, mengakses, menjalankan, dan

mungkin menyangsikan penggunaan basis data.

2. BASIS DATA MULTIMEDIA

a. Data Multimedia:

Ada sejumlah tipe data yang dapat disebut sebagai tipe data multimed ia.

Terdapat elemen-elemen klasik yang digunakan sebagai massa bangunan dari

platform, lingkungan, atau alat integrasi multimedia umum hub yang

digunakan. Berikut ini adalah tipe data dasar yang ditemukan dalam sebuah

basis data multimedia tipikal, termasuk:

i. Teks: bentuk di mana teks dapat disimpan dengan sangat bervariasi;

ii. Audio: digenerasikan dari sebuah perangkat rekaman auditor;

iii. Gambar: hitam dan putih, berwarna, peta, fotografi, dan lukisan;

iv. Objek grafis: lukisan umum, sketsa, dan ilustrasi, atau objek 3D;

v. Rangkaian animasi: gambar atau objek grafis yang biasanya

digenerasikan secara independen;

vi. Video: juga merupakan rangkaian sebuah gambar, disebut frame, tetapi

merekam sebuah kejadian kehidupan nyata secara tipikal dan biasanya

diproduksi menggunakan perekam video; dan

vii. Multimedia komposit: dibentuk dari sebuah kombinasi dua atau lebih

tipe data di atas, misalnya campuran audio dan video dengan keterangan

tekstual.

Berbagai tipe data multimedia seperti audio, video, dan rangkaian animasi juga

memiliki persyaratan kronologis, yang mempengaruhi penyimpanan,

manajemen, sebagaimana presentasinya. Penggunaannya menjadi semakin

bertambah saat berbagai tipe data dari mungkin sumber tidak bersangkutan

harus ditawarkan pada waktu yang diberikan. Demikian juga data grafik,

gambar, dan video memiliki batasan spasial dalam kaitan dengan kontennya.

Potensi data bervolume besar menjadi bagian dalam sistem informas i

multimedia semakin jelas ketika mempertimbangkan, sebagai contoh, sebuah

gambar bergerak dapat berjalan selama dua jam, dan video klasik peperangan

akan mengakomodasi ribuan bioskop. Sebuah pepatah luhur mengatakan bahwa

suatu gambar lebih bernilai daripada ribuan kata.

Atribut tambahan dari informasi multimedia adalah bahwa antarmuka dengan

semacam tipe informasi biasanya menyangkut fungsi jangka panjang (seperti

data video), dengan banyak potongan klien tunggal (seperti dalam pengaturan

dukungan bersama). Dan sebaliknya, dalam pengaturan yang diselenggarakan

dengan tujuan bersama, mayoritas data multimedia akan dapat diakses dalam

sebuah bentuk baca saja. Asumsi ini dapat digunakan untuk memfasilita s i

ketetapan persetujuan algoritma pengontrol.

b. Bagaimana Teknologi Multimedia digunakan secara berbeda dalam Basis

Data

Secara teoritis itu harus layak untuk mengobati multimedia Database dengan

cara yang sama sebagai data yang didasarkan pada data jenis (misalnya: tanggal,

angka dan karakter), Namun demikian, terdapat beberapa tantangan yang terjad i

sebagai hasil data multimedia, tantangan ini adalah:

i. Dalam kasus database audio dan video, waktu untuk mengambil

Informasi mungkin sangat penting misalnya, video on order.

ii. Data Multimedia besar sehingga mempengaruhi penyimpanan,

pengolahan, pengambilan dan transmisi multimedia Data sebagaimana

tercantum dalam database.

iii. Substansi data multimedia sering ditangkap dengan beragam

"menangkap" prosedur (untuk Misalnya, pengolahan gambar) yang

mungkin lebih diandalkan. Teknik pengolahan Multimedia perlu

mampu menangani beragam cara menangkap konten termasuk cara

manual dan atau metode otomatis.

iv. Query yang dibuat oleh pengguna di database multimedia berulang kali

tidak dapat kembali dengan jawaban tekstual. Sedikit, tanggapan untuk

permintaan mungkin multimedia yang kompleks presentasi bahwa

pengguna dapat melihat melalui di / nya waktu luang. Dengan demikian

berbagai garis menunjukkan bagaimana query ke database multimed ia

dapat digunakan untuk membuat presentasi multimedia yang memenuhi

permintaan pengguna.

v. Dalam database konvensional, pengguna secara eksplisit menyerahkan

Nilai titik objek dimasukkan ke dalam database; ini adalah ekstraksi fitur

otomatis dan Indexing Modus.

vi. Relatif, memanfaatkan alat-alat canggih seperti image pengolahan dan

pengenalan pola alat untuk gambar, untuk mengekstrak berbagai elemen

dan konten multimedia benda. Sebagai ukuran data menjadi sangat

besar, ada perlu untuk struktur data khusus yang akan digunakan untuk

menyimpan dan mengindeks data tersebut.

c. Pendekatan Dasar untuk Penerimaan Data

Manajemen database memiliki membentang sejarah banyak dan banyak

pendekatan telah diciptakan untuk mengelola dan query beragam jenis database

dalam sistem manajemen database, pendekatan dasar yang dimohonkan

manajemen database dapat dikategorikan ke dalam jenis-jenis berikut:

Sistem database konvensional: ini adalah Metode luas digunakan

untuk mengelola dan mencari melalui database untuk data terstruktur.

Semua data dalam database Sistem demikian harus mematuhi aturan

yang telah ditetapkan beberapa struktur dan pemeriksaan (yaitu, skema).

Untuk mempersiapkan query database, pengguna database tersebut

harus memberikan Data yang objek harus diambil, database tabel dari

mana mereka harus diekstrak dan predikat di mana pengambilan

didasarkan. Sebuah bahasa query untuk Database umumnya akan

menjadi jenis buatan, satu dengan dikontrol sintaks dan kosa kata,

seperti SQL.

The Information Retrieval (IR) sistem: sistem IR majorly digunakan

untuk mencari koleksi teks besar dalam Database, di mana teks data

digambarkan oleh pengindeks menggunakan kata kunci atau abstrak

tekstual, dan kata kunci atau bahasa alami yang digunakan untuk

mengekspresikan permintaan tuntutan. Misalnya untuk gambar atau

video yang kita harus menggambarkannya dengan kata-kata atau dengan

cara perlu menyimpan banyak metadata dalam bentuk tekstual.

Konten Berbasis Retrieval (CBR) Sistem: Ini Pendekatan yang

digunakan untuk mengambil objek multimedia yang diinginkan dari

kelompok besar berdasarkan fitur (seperti tekstur, bentuk, warna, dan,

dll) dari database yang dapat secara otomatis diambil dari obyek itu

sendiri. Meskipun kata kunci dapat diperlakukan sebagai "fitur" untuk

teks data, pencarian informasi tradisional memiliki lebih banyak kinerja

lebih tinggi dari pengambilan berbasis konten karena kata kunci

memiliki kemampuan terbukti untuk mewakili semantik, sementara

tidak ada fitur telah menunjukkan meyakinkan semantik Kemampuan

menjelaskan. Namun kelemahan utama dari metode ini adalah bahwa ia

tidak memiliki presisi.

Pola Grafik atau pohon yang cocok: Pendekatan ini bertujuan untuk

mengambil objek sub-grafik dari objek grafik menurut beberapa pola

dilambangkan ditentukan.

d. Metadata

Klasifikasi metadata untuk mendapatkan konsep yang sangat cocok bantu

dalam mengeksplorasi metadata. Dengan demikian, metadata dapat

diklasifikasikan:

i. Ketergantungan pada klasifikasi konten

Content-independen metadata: Jenis rincian Informasi yang

tidak bergantung pada isi Dokumen dengan yang terkait

dengan. Contoh jenis ini adalah lokasi, jenis-of-sensor yang

digunakan untuk merekam dan modifikasi-tangga l

dokumen. Ada yang ada konten informasi yang ditangkap oleh

metadata ini tetapi mereka masih berguna untuk pengambilan

dokumen dari lokasi fisik mereka yang sebenarnya.

tergantung Content-metadata: Tipe ini tergantung pada isi

dokumen itu terkait dengan. Contoh konten metadata tergantung

yang max-warna, ukuran dokumen, jumlah baris dan kolom

dalam gambar. Konten tergantung metadata bisa menjadi sub-

dibagi lebih lanjut ke: -

metadata berbasis konten Direct: Tipe ini didasarkan

langsung pada isi dokumen. A Contoh populer ini indeks

teks lengkap berbasis pada teks dokumen. Pohon terbalik

dan Dokumen [Christos Faloutsos] vektor adalah contoh

dari jenis metadata.

Isi deskriptif metadata: Jenis menggambarkan isi

dokumen tanpa langsung pemanfaatan tersebut

isinya. Ini sering melibatkan penggunaan pengetahuan

atau manusia persepsi / kognisi. Contoh dari ini adalah

penjelasan tekstual yang menjelaskan isi dari suatu

gambar. Tipe ini datang dalam dua rasa:

i. Domain-independent metadata: Ini metadata

informasi capture hadir dalam Dokumen yang

independen dari aplikasi atau domain subjek

informasi. Contoh ini adalah C / C ++ mengura i

pohon dan definisi tipe dokumen HTML.

ii. metadata Domain-spesifik: jenis metadata ini

dijelaskan secara khusus untuk aplikasi atau

domain subjek informasi. Contoh metadata

tersebut tutupan lahan dari GIS dan populasi dari

Sensus domain. Dalam kasus data struktural,

database Skema adalah contoh metadata tersebut.

Contoh lain adalah domain spesifik ontologi,

istilah yang dapat digunakan untuk membangun

metadata spesifik untuk domain.

ii. hirarkis Klasifikasi Berbasis

Ini adalah jenis lain dari klasifikasi metadata yang mungkin seperti yang

diusulkan oleh Gilliland-Swetland (1998):. Klasifikasi ini meliputi:

Deskriptif: merupakan metadata yang digunakan untuk

mengidentifikasi atau menjelaskan sumber daya informasi.

Teknis: adalah metadata yang terkait dengan bagaimana fungs i

sistem atau berperilaku metadata.

Administratif: adalah metadata yang digunakan dalam

mengelola dan mengelola sumber daya informasi.

Pelestarian: adalah metadata yang terkait dengan manajemen

pelestarian sumber daya informasi.

3. MANAJEMEN LAYANAN TI DAN TEKNOLOGI MULTIMEDIA

Secara umum, sistem manajemen database multimedia Aplikasi dapat dibangun di

mana pun ada kebutuhan untuk mengelola data multimedia biaya efektif. Sehubungan

Dengan Itu multimedia DBMS telah menemukan aplikasi dalam bervariasi seperti

daerah sebagai kesehatan (telemedicine, kesehatan terpadu manajemen informas i,

sistem citra medis), pendidikan (Digital library, pelatihan, presentasi, pembelajaran

jarak jauh), hiburan (video-on-demand, database musik, interaktif TV), informas i

penyebaran (Berita-on-demand, iklan, siaran TV), dan manufaktur (didistribus ikan

manufaktur, didistribusikan authoring kolaboratif). Demikian daerah lain aplikasi dapat

terdiri dari keuangan, e- perdagangan, penerbitan elektronik, informasi geografis

sistem, konferensi video, dll.

Sejumlah DBMS multimedia yang sudah ada. Kebanyakan dari mereka adalah

lampiran dari relasional ada atau object DBMS berorientasi. Kompetensi multimed ia

yang ada DBMS dapat dinilai oleh sejauh mana mereka bisa mendukung jenis media

yang berbeda (terutama gambar dan video). Mereka juga dapat dievaluasi dengan

kemampuan mereka untuk mendukung khusus fungsionalitas yang diperlukan dari

sistem database untuk mengelola data multimedia, seperti pengiriman real-time dan

konten berbasis query dan pengambilan. Sayangnya, sebagian besar yang ada DBMSs

multimedia gagal ini. Meskipun demikian, ketat penelitian beragam sedang diarahka n

berbagai bagian masalah dan dengan demikian diharapkan bahwa sistem baru dengan

kemampuan yang lebih tinggi dan lebih baik dalam waktu dekat akan muncul. Tren

masa depan termasuk melakukan pengindeksan, pencarian, dan menjelajah langsung

pada data terkompresi, terutama untuk video Data; manajemen data video; bahasa query

multimedia; kerangka pengindeksan seragam untuk tipe data yang berbeda; gambar dan

pengambilan video yang berbasis konten; dan multimedia transportasi dan pengiriman

melalui Internet.

4. KESIMPULAN

Data multimedia harus disimpan dengan data lanjutan struktur dan dengan bantuan

metadata untuk membuatnya pencarian dan pengambilan proses sederhana. Dengan

demikian pendekatan pada bagaimana gambar dapat disimpan dengan menggunakan

struktur data dan dapat dicari telah diperiksa. Struktur data ini membantu menghapus

atribut dari data seperti foto atau video sehingga kita bisa mengeksekusi query berbasis

konten. Juga keuntungan dan Kerugian dari struktur data tersebut dibahas. Namun,

terkadang proses pengindeksan dan pencarian mengkonsumsi banyak waktu dalam

kasus database besar. Jadi kita butuh bantuan metadata untuk membuat proses yang

lebih cepat yang tidak tidak memerlukan penggalian karakteristik dan informasi dari

Data itu sendiri. Disajikan juga adalah bagaimana metadata yang dihasilkan dan

disebutkan beberapa masalah yang harus dilakukan. Juga bagaimana metadata dapat

diklasifikasikan sehingga tergantung pada konteksnya, lebih baik menggunakan dapat

dibuat. Juga bagaimana metadata standar bisa membantu pemanfaatan penggunaan

metadata. Secara umum, multimedia aplikasi dan sistem database multimed ia

terdistribusi khususnya, mengangkat beberapa isu baru dalam semua aspek sistem

komputer, kisaran tersebut dari sistem operasi ke jaringan untuk perangkat keras

umum. Tersedia secara luas sistem operasi tidak mendukung operasi real- time

secukupnya. Agak, mereka menawarkan hardware depan berakhir untuk

menyampaikan dan menyajikan data multimedia. Beberapa multimedia data, seperti

media terus menerus, mungkin memerlukan real-time pengiriman dan presentasi,

sedangkan syarat real-time mungkin tidak sekaku yang ditemui dalam sistem real- time

keras. Oleh karena itu, sistem database multimedia tidak bisa sepenuhnya menyediakan

fungsi sampai dukungan untuk real-time Data media terus menerus menjadi bagian

integral dari sistem operasi.

Aplikasi Teknologi Multimedia dalam Manajemen Layanan Basis Data dan Teknologi Informasi

Education

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