How to Govern Open Data ? The politics of open data portals.

Antoine Courmont Centre d’études européennes (CEE) / Sciences Po

antoine.courmont@sciences-‐po.org

How to Govern Open Data?

The politics of open data portals

Paper presented at the IPSA Conference, Madrid, July 8-‐12, 2012.

Panel: Open Government

Draft paper, please do not cite without the author’s permission.

Abstract:

Using a comparative overview of the open data portals, this paper analyses the open data portals as a means of regulation of the released data. In a first part, it shows how legal, economic and technical mediations may interact to enable or restrain the re-‐uses of public data. The pluralism of ways to regulate data is pointed out. In a second part, it describes the relationships between governments and their constituents defined by the alignments of those mediations. It argues that three models of open data portals are emerging: the pipe model, the platform model and the multi-‐front approach model.

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This paper presents a preliminary analysis of open data portals as instruments of regulation of public data. Drawing on the work that is very much in progress, this essay is quite fragmented. The ambition of the current paper is limited to testing its hypothesis and research questions.

Introduction

Information and data are key tools of government. Governments gather large amounts of data in order to know their territory, population and society and to act upon them. Without data, there is no public policy. Since few years, Public Sector Information (PSI) and Freedom of Information (FOI) lobbies have pressured governments to open access to their data to promote transparency and commercial re-‐uses. The US and British initiatives have launched an international movement of setting up governmental open data portals all over the world. Actually, opening access to data tends to become a legal obligation for public administrations.

However, administrations could be reticent to open access to their data. Indeed, it means lose their monopoly on public data. This exclusive control was a source of power, and governments are reluctant to lose authority and influence. Most of all, opening public data raises some risks for governments (Bannister et Connolly, 2011). Firstly, transparency reveals the functioning of the state apparatuses of power and may force them to explicit their action. Open government data threatens the formal functioning of power and citizens may lose confidence in state action. Secondly, re-‐uses of public data might be potentially in contradiction with governmental actions and differ from the common purpose sought by public policies. For instance, while a local government is promoting the use of public transport, a developer, thanks to public data of traffic jam, could create an app that encourages car traffic. In addition, released data may “empower the empowered” (Gurstein, 2011) rather than strengthen citizen engagement in policy. Thirdly, data are always produced in order to fulfill a specific need. There is a strong link between the method of production of the data and the privileged form of intervention (Desrosières, 2003 ; Didier, 2009), which allows the consolidation of the aggregate. This stabilization gives consistency and relevancy to the data. And yet, opening public data makes the data unstable. Indeed, the chain between process and use of the data is broken up, since there is a possibility of using differently the data. So, opening data access may threaten the reliability and the accuracy of the data. For all these reasons, open data is full of uncertainties and may frighten governments. That’s why they are looking to reduce this uncertainty and to regulate the released data.

Open data programs mark the transition from a logic of government to a logic of governance, in which public authorities regulate society rather than governing it, allowing a larger participation of social and economical actors. This reordering of power doesn’t mean a decline of public authorities, but on the contrary, public authorities that gives the rules in a logic of regulation of the society. In this context, I will present in this paper some modalities of governing open data implemented by public authorities and the different forms of relationships between governments and their constituents they imply. But for that, it’s necessary to admit that there is a range of ways opening governmental data.

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Defining open data

In December 2007, Tim O’Reilly, Lawrence Lessig, Carl Malamud, David Moore and others theorists of Internet and Free culture, established a list of principles of open government data. After two days of work, they defined 8 principles1:

1. Data must be complete

2. Data must be primary

3. Data must be timely

4. Data must be accessible

5. Data must be machine processable

6. Access must be non-‐discriminatory

7. Data formats must be non-‐proprietary

8. Data must be license-‐free

These 8 principles became the basis of the canonical definition of open government data. They have been used to define what open government data should be and to evaluate governmental initiatives. However, this list is quite restrictive and limits governmental possibilities of opening data. It follows the tradition of the open source movement, which adopts a restrictive definition of the adjective “open”. This paper will break up with this normative definition and follow an extensive interpretation of open government data to point out the diversity of governmental choices. Open data means all initiatives by public authorities of making their data available to a wide audience. This definition allows thinking diversity and pluralism in the way of opening data. Our hypothesis is that these various modalities of publishing data represent different modes of open data governance.

Open data portals as political objects

By liberating its data, governments must adopt indirect modalities of regulation to restrain the possibilities of uses of these datasets. In his book Code is law (Lessig, 2006), Lawrence Lessig points out four modalities of regulation that interact to constrain individuals: law, social norms, markets and architecture. As expressed in the title, he argues that, in cyberspace, computer code, a subspecies of physical architecture, may regulate conduct as well as legal code. However, as a modality of regulation, code has some particularities: it is automated, immediate, plastic and, above all, it can regulate without transparency (Grimmelmann, 2005). Lawrence Lessig assumption’s invites to take into consideration technical architectures as political objects. This paper will focus on legal, economical and, especially, technical aspects of open data portals2.

Open data portals are websites used to release public data. They are the interfaces between governmental data on one side and re-‐users on the other side. They act as a

1 http://www.opengovdata.org/home/8principles 2 I will leave aside social norms as a way of regulating open data since they don’t have a major impact at the level of the open data portals.

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gateway between these two sides. As interfaces, open data portals must be considered as infrastructures. Far from being confined to simple technical considerations, infrastructures are not neutral (Hughes, 1989). On the contrary, they have an inherently political nature. Indeed, potential practices are inscribed in the deepest levels of design of infrastructure. That’s why open data portals “do” something. They enable or restrain actions and define a field of possible uses of released data. This lack of neutrality justifies considering open data portals as political objects, which contribute to the governance of released data.

The political nature of infrastructure is “a call to study boring things”(Star, 1999), such as technical aspects which tend to be invisible and so, ignored. In this paper, I will focus on some of these mediations involved on open data portals, which enable to link governmental data and their re-‐users. As Antoine Hennion pointed out, the concept of mediation differs from the one of intermediary, since it implies a “strategic relation that defines at the same time the terms of the relation and its modality” (Hennion, 1993). Indeed, they establish the relationship between public data and their re-‐users, and they define the modality of the relationship.

The comparative approach to open data portals reveals a diversity of ways in which the governmental data is released3. To study those different ways and their political implications, I will use the model of the pluralist compass theorized by Dominique Boullier (Boullier, 2003, 2008). Derived from the works of Bruno Latour (Latour, 1997) and Isabelle Stengers (Stengers, 1996), this compass crosses two axis: attachments/detachment and certainties/uncertainty. It allows to describe the diversity of the possible mediations and to better understand their contrasts4. Its aim is not to narrow the range of possibilities, but, on the contrary, to open up the political debate on open data portals.

This paper comprises two parts. Firstly, I pose the question of how legal, economical and technical mediations contribute to a comprehensive understanding of open data portals as means of regulation of released data. Secondly, I point out some alignments of these mediations and ask how these alignments define the relationship between governments and their constituents.

3 To make our analysis, we have selected a representative sample of open data portals: French local governments (Paris, Rennes, Toulouse, Nantes, Montpellier, Bordeaux, Saône et Loire), European (London, Manchester, Leeds, Bruxelles, Berlin) and North American cities (New-‐York, San Francisco, Chicago, Boston, Seattle, Edmonton, Vancouver, Toronto, Ottawa, Montréal). 4 As Dominique Boullier said (Boullier, 2012), this compass “forces an identification of all the positions, even those which are sometimes hardly expressed, in order to bring to the fore possible choices which may have been overlooked or crushed by the obviousness of others. It is therefore, first and foremost, a heuristic tool and not a system for definitive classification and storage”.

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Legal, economical and technical mediations as means of regulation

1. Pluralism of legal architectures

The first modality of regulation of free data is the legal aspect, i.e. the juridical architecture. Law is the first modality of regulation from the State. The legal licenses that regulate released data are relatively well known. I’d like to briefly go over four licenses that may be placed on a permissive continuum: public domain model, authorship model, copyleft model and restrictive license. Two criterions distinguish these licenses: on the one hand, the obligation to credit the data producing entity, on the other hand, the lack of certainty about the legal framework of the reused data.

The public domain model lays down no limitation to the re-‐users5. Data are considered as belonging to the public domain. This most permissive license offers no means of control for the government.

The authorship model allows all uses of the data provided the authorship is mentioned (BY). The French “Open License” and the British “Open Government licence for public sector information” are such licenses.

The copyleft model requires to credit the source and to preserve the same rights in modified versions of the data (BY + SA). This obligation to share-‐alike the modified datasets is a way for the governments to obtain a feedback on uses of their data and possibly to benefit from these improvements.

The last kind of license is the most restrictive. Re-‐users must, as the previous one, credit the source and share-‐alike the dataset, but they can’t transform the dataset (BY + SA + ND). This license is very rarely used since these constraints are in opposition to the aims of reuses of open data. Nevertheless, some governments insert in their license a relatively vague clause of no-‐alteration of the data and no denaturing of their meaning6. If this clause doesn’t prevent the transformation of the data, it establishes a restrictive legal framework that enables governments to greatly restrain re-‐uses of released data.

5 For instance, the PDDL license: “Public Domain for data/databases”. http://www.opendatacommons.org/licenses/pddl/1-‐0/ 6 For instance, it’s the case of the license of the French city of Rennes.

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2. Pluralism of economic models

The second way governments have to restrain uses of data is through the economic model of the data. I don’t want here to enter into the debate of the costs of collecting, producing and publishing data, neither on the sale of public data by administrations to make profit. I only focus on the economic models as a means of regulation. Market is here used to regulate the use of public data. I know that canonic definition of open data stipulates that this information should be available for free. Nevertheless, governments may choose to sell their data in order to limit and control access to it. I distinguish here three possibilities7, which differ in the fact they constitute an economic barrier to entry and they enable governments to keep an explicit link with the clientele of re-‐users.

2.1. Allowance

Re-‐users who want to use a public dataset have to pay an allowance to the administration, upon a variable scale previously established (depending on the cost of publication, the “value” of the data, the sales generated by the re-‐user). The fee for access greatly limits the availability of the information and restrains it to actors, which are able to afford it. Furthermore, governments keep full control of their data as they may choose the actors they would be able to use the data.

The allowance model, which was the norm in the administration, tends to become the exception. For instance, in France, a bill, published the 27th may 2011, told that gratuity

7 Another possibility might be a purchase per unit solution. The re-‐user would purchase only one part of the dataset. As far as we know, any governments have not implemented this model.

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is the rule. Public data producers must justify the direct monetization of their data. A list of fee-‐paying data will be established. Each data that will not be on this list will be free by default.

2.2. Freemium

Data may also be free by default, but fee-‐paying depending on their use or on their wished access. For instance, commercial uses can be submitted to an allowance, or a tax is imposed to access the data if re-‐users exceed a fixed ceiling of use. For instance, an API might be free to attract developers, and then fee-‐paying beyond a fix number of requests (and so beyond a significant success of this service).

2.3. Free

Public data may be published freely, without any constraint linked to the type of re-‐use or the marginal cost of opening the data. Supporters of gratuity legitimate it by the fact that public data has already been fund by the tax. By monetizing this data, re-‐users would pay two-‐times the data. When they release freely their data, governments lose all control over their data.

3. Pluralism of technical architectures

Since Winner’s classic paper “Do Artifacts have Politics?” (Winner, 1986), it’s recognized that “technical things have political qualities” and that “they can embody specific forms of power and authority”. That’s why it is necessary to pay attention to the technical characteristics of open data portals and the meaning of those characteristics. Due to the

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limits of this paper, I will only focus on three technical aspects: data access, data hosting and data formats8.

3.1. Data access

Four kinds of access to the data are possible: no-‐selective feed, bulk download, atomic data and selective feed. Two criterions distinguish these four types of access. First, they offer either a file or a feed. A feed maintains a strong link with the producing entity of the data, whereas a file leads to a detachment from it. Second, these four solutions differ in their respect of the integrity and the structure of the dataset.

3.1.1. No-‐selective feed (RSS)

RSS (RDF Site Summary) allows automatic re-‐uses by websites and programs. It’s a well-‐known format, which can be used to publish data. It offers a control over the data and restrains re-‐uses, since re-‐users can’t modify data obtained through a RSS feed. It’s a no-‐selective feed: developers must use the dataset as a whole, they can’t select some data, and there is no data processing. Thus, the integrity of the dataset is respected. For instance, the Socrata’s platform (used by New-‐York, Chicago, Seattle) allows a RSS export of all the dataset.

3.1.2. Bulk download

The most common modality of accessing data is downloading the dataset file from a remote server to a local storage disk. Direct download is the simplest solution to open up data. However, once the dataset has been downloaded, governments lose all means of control over it. Administrations have no idea who and what users are doing with their data. Users can easily modify, transform, and manipulate the dataset. Administrations only know the number of downloads for each file. If the dataset is modified, re-‐users must download it again to update their application. So, with this modality of opening data, there is a risk of an uncontrolled dissemination of public data and of a use of stale data.

3.1.3. Atomic data

Governments can also publish their data preliminary extracted from the dataset. Re-‐users have only access to a part of the dataset. Indeed, it might be broken into several subsets (for instance, in relation to different geographic locations). So, the dataset’s integrity isn’t respected.

3.1.4. Selective feed (API)

Some open data portals provide access to their data through an API (Application Programming Interface). API allows direct access to the data: an application automatically requests another application the data it needs. It makes practically impossible a mass dissemination of public data. Nevertheless, contrary to the RSS feed, the application can choose to use only some data of the dataset. So, the dataset integrity is not always respected. Access to the data is furnished as a feed: dataset are

8 Other technical mediations could be analyzed to complete this study, for instance: the data structure (unstructured, semi-‐structured, structured), the data granularity, and the data released time (immediate, recent, delayed, archive).

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automatically updated and the administration can stop the access to the feed. Moreover, access to the data trough an API is registered as logs. That’s why API allows a fine control of the accesses, their potential limitation, a monitoring of the use of the service by the applications and a guaranty that all the re-‐users are using the accurate version of the dataset. Finally, developers must sometimes be registered to use the API. Re-‐users are dependent on data producers: if they decide to stop the API, the accessibility chain is broken up, the application don’t receive data anymore.

3.2. Data hosting

As for the previous aspect, I will distinguish four kinds of data hosting: internal hosting, cloud hosting, peer-‐to-‐peer and external platform. Each of those solutions differs in the capacity for the administration control the whole of the opening process and to keep a hold over the released data (for instance, the more or less easily abilities of removing or replacing the dataset). Moreover, the data hosting raise the issue of the visibility of the governmental open data program. Indeed, by publishing their data through the peer-‐to-‐peer networks or a multi-‐actor platform, governments suspect their action will not have a sufficient visibility and their relationships with re-‐users will be limited.

3.2.1. Internal hosting

The administration develops its own platform and stores its data in its own servers. Platform solutions to publish data are various. Several are in open-‐source, such as the content management platform Typo3 developed for the French city of Rennes and used by the city of Nantes, or the CKAN (Comprehensive Knowledge Archive Network) solution, proposed by the Open Knowledge Foundation. With these solutions, governments keep the entire control of its data.

3.2.2. Cloud hosting

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Another possibility for the administration is to use a SaaS solution (Software as a Service). The platform, created by an external company, is hosting – as well as the data – in the cloud. This actually is the easiest solution since it requires any technical needs. Moreover, the administration keeps all its right over its data. Nevertheless, it loses the control over the location of its data. Data are stored in external servers, what could cause legal problems. Moreover, the administration doesn’t have any guarantee of the evolution of the SaaS and is dependent on the SaaS company.

3.2.3. Peer to peer

Another way to store data is to share the file through a peer-‐to-‐peer network. For instance, Great Britain chose this solution to release its financial data. The distributed architecture reduces the bandwidth and storage costs: peers are both suppliers and consumers of resources. Nevertheless, the lack of a centralized server prevents the administration from controlling diffusion and use of its data.

3.2.4. External platform

The last possibility is to commit its data to an external multi-‐actors portal. For instance, in France, the national website data.gouv.fr hosts the data of the towns of Coulommiers, Saint-‐Quentin and Longjumeau. By sharing the platform, administrations lose their independency and their abilities to choose the means of publishing their data. All the technical aspects are assigned to the designers of the external platform.

3.3. Data formats

Formats are another way to limit the boundaries of what is possible to do with the data. There are many kinds of formats, and the selection of one of it depends on the type of data (statistical, geographical…). However, four categories of formats may be basically distinguished: PDF, closed and proprietary formats, open and free formats and API. The interoperability they allow and the integrity of the dataset they respect distinguish them.

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Contrary to the previous analyzed technical aspects, it is a no-‐contradictory policy: some open data portals offer different formats for each dataset9.

3.3.1. PDF

Publishing data as PDF documents greatly limits the ability for others to reuse that data. Indeed, while humans can read PDF documents, they are very hard for a computer to use. The stability of the presentation of PDF format produces a foreclosure effect, preventing interoperability.

3.3.2. Closed and proprietary formats

Publishing data as closed and proprietary formats (for instance, .xls or .doc) limits the re-‐uses, by restricting interoperability. Moreover, the owner of the format can restrict the use, impose users a royalty on the use or intimidate legally the developers of applications using it. So, a proprietary and/or closed format creates a barrier for access.

3.3.3. Open and free formats

Open formats are standards established by public authorities or international institutions, whom aim is to set norms to ensure interoperability between software. No entities have an exclusive control on this format, which are designed for an automatic processing. For instance, the CSV format (Comma Separated Values) stores tabular data in plain-‐text form; each entity is separated by line breaks. Others common open formats used to publish public data are XML or RDF. Thus, providing open machine-‐readable formats allows greatest re-‐use, and so, less modalities of control for governments.

3.3.4. API

Another alternative for governments is to publish their data through an API. An API allows large re-‐uses of datasets. Interoperability is maximal since the API enables an automatic exploitation of data while the other formats require mediation to be used. However, contrary to the open formats, publishing data with an API prevents any modification of the dataset structure, what preserves the accuracy of the data10.

9 In addition, the choice of a format depends on the technical abilities of the administration and on the software they use. This phenomenon of path dependency leads to political decision by default. 10 To complete this analyze, API formats (XML, JSON, SOAP, REST) should also be taken into consideration. It is possible to subdivide the general category “API” to another compass with four types of API available.

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Technical architectures and mediation alignments

I have outlined some of the mediations, which take part in the linkage between public data and their re-‐users on the open data portals. The nature of these mediations is very heterogeneous: they are legal, economic and technical. After having explored the diversity of the mediations, it’s now necessary to examine the forms of stability, which are emerging. Indeed, although several mediations are possible, not all of which are compatible. That’s why compromises between the different means of regulation must be established to hold public data and their re-‐users in a coherent way. Some of these mediation alignments will be outlined to define more precisely the nature of the relation they define (Hennion, 1993). Three types of portals may be sketched out: the pipe model, the multi-‐front approach model and the platform model11.

11 These three models constitute in this way ‘ideal types’. Every open data portals may not fall neatly into one of the models. However, they do help make visible the divergences between different types of open data portals and so to analyze open data governance. This work is in progress and the political implication of those models should still be developed. Moreover, we need to be cautious and to not make definitive judgments since these process are still unstable and questioned by the actors themselves.

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Pipe model Platform model Multi-‐front approach model

License12 BY or SA + BY BY or SA + BY BY or SA + BY

Economic model12 Free Free Free

Data access Bulk downloading (files) API (feed) Pluralist (files +

feed)

Data formats Closed or open formats API Diversity of formats

Data hosting Internal hosting Internal or cloud hosting Cloud hosting

Political implication Uncertainty Accessibility and control Pluralism

Target audience Larger audience Developers Pluralist

Nature of the relationship between

government and re-‐users

Vertical Collaboration Vertical and/or collaboration

Table 1: Mediation alignments and political implications

1. The pipe model

The pipe model is a single access point, which offers a bulk downloading of the dataset. It’s the traditional and the easiest way of publishing governmental data. Most of open data portals fall into this model. The simplicity of access to the data enables a large audience to use the data. Indeed, download doesn’t need users to be a developer and to have a lot of specific software to handle data 13, especially when the open data portals integrate a module of direct interaction or of visualization of the dataset14.

However, the pipe model is quite uncertain for governments since they can hardly limit reuses of the data after having released it. Once the dataset has been downloaded, 12 A large majority of open data portals are publishing their data freely and under authorship (BY) or copyleft (SA + BY) models. However, although there are the most common solutions, some governments might choose other possibilities, as, for instance, a freemium access to the data. 13 Nevertheless, the unequal ability of understanding the data greatly restrains the appropriation of data by a wide audience and encourages the apparition of “intermediaries of open data” (Mayer-‐Schönberger et Zappia, 2011 ; Davies, 2010 ; Gurstein, 2011 ; Peugeot, 2012). 14 This aspect was not analyzed in this paper as a modality of access the data. However, several portals offer, in parallel with the download, an insight of the dataset (with some modules of datavisualization) as, for instance, the open data website of the French department of Saône et Loire (http://www.opendata71.fr).

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administrations have no idea who and what users are doing with their data15. The relationship between governments and re-‐users defines by this type of open data infrastructure is a vertical one. The model of government is quite as a “vending machine government” (O’Reilly, 2010). It is similar to a supply and demand relationship, with on one side governments, which provide the data, and, on the other side, users, which consume it.

2. The platform model

The platform model is inspired by the current transformation of website and software companies into service-‐oriented architecture. Platform architectures are gateway technologies that permit multiple systems to interoperate. Governments don’t just provide an open data website, they provide open data web services. These services are governmental software development kit (SDK): APIs that offer an opportunity for citizens and companies to build applications based on these data. The strategy of the platform is to seek to leverage the time and the expertise of a globally distributed community of developers16. The platform model allows a great accessibility to the data for the developers while giving administrations the opportunity to control re-‐uses. It subscribes in a strategy of collaboration and co-‐creation between governments and developers. The objective is to develop an ecosystem, a community of developers with whom governments can share and interact. However, publishing data through an API restrains the re-‐uses to actors who have the technical abilities to handle this type of architecture. So, the open data platform targets a smaller audience than the pipe model.

With this aim in mind, the American government wants to transform its open data website data.gov to an open data platform. On May 23, the White House issued a directive that requires all agencies to establish programming interfaces for internal and external developers to use, and make “applicable Government information open and machine-‐readable by default”17. All data should be available through web APIs by default. The American government seeks more interoperability and consistency in the manner it delivers information. This directive follows the recommendation of Tim O’Reilly to constitute a “government as a platform” (O’Reilly, 2010).

3. The multi-‐front approach model

The multi-‐front approach model is a pluralist one. It shares characteristics with both of the two previous models. Indeed, designed by specialized companies, it offers both bulk downloading and API access to the datasets. Moreover, data are available in several formats. Several North American cities (New-‐York, Chicago, Seattle…) have chosen the SaaS solution provided by the company Socrata to publish their data through this type of pluralist portals.

15 Actually, governments seek tracking the uses developers make of their data through other apparatus, such as the organization of hackathons or open data contests. The analysis of these events as means of regulation is yet to be done. 16 This strategy has been successfully developed by IT companies, such as Apple with its App Store, or Facebook with the Facebook platform. 17 http://www.whitehouse.gov/sites/default/files/omb/egov/digital-‐government/digital-‐government.html

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Conclusion: what arena of discussion of these political choices?

The purpose of this paper was to demonstrate that governments could regulate their released data through their open data portals. By exploring different mediations, I showed that political principles are inscribed into the design of those infrastructures and that a political pluralism of open government data was possible. Then, I pointed out three alignments of these mediations: the pipe model, the platform model and the multi-‐front approach model. I argued that each of those models defined a different relationship between governments and their constituents. These three types of open data portals are compatible with the principles established by the group of Sebastopol, which constitutes the benchmark definition of open data.

The pluralism of possible mediations and the diversity open data portals emphasize the fact that different political choices are possible in the way of opening governmental data. However, there are few arenas of discussion of these political choices. The mediations seem imposed by public authorities without any debate, although few organizations from civil society try to get their point of view across18. The analysis of these groups, their forms of action and their influence on the governmental open data strategies is yet to be done.

Finally, I would like to mention that infrastructure is a relational concept, which must be studied in relation to organized practices (Hughes, 1989 ; Star et Ruhleder, 1996). This paper focuses only on the mediations that intervene in the open data portals, without taking into consideration the social groups who design and practice those infrastructures. This relational characteristic avoids falling into a technological determinism. Once the infrastructure has been conceived, the distribution of power is not definitely established. On the contrary, as all technical devices, open data portals are hackable and changeable. As they produce patterns of power and authority, they may also encounter resistance. The confrontation with users may reinvent and reshape these infrastructures (Akrich, 1992). The study of the open data portals in relation with their environment is necessary to complete the analysis of the politics of open data portals.

18 For instance, The Guardian, the Sunlight Foundation, the Open Knowledge Foundation (OKFN), Regards Citoyens and the FING (Fondation Internet Nouvelle Génération).

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How to Govern Open Data ? The politics of open data portals.

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