Thought experiment: a data extraction transparency initiative

[Summary: rapid reflections on applying extractives metaphors to data in a international development context]

In yesterday’s Data as Development Workshop at the Belfer Center for Science and International Affairs we were exploring the impact of digital transformation on developing countries and the role of public policy in harnessing it. The role of large tech firms (whether from Silicon Valley, or indeed from China, India and other countries around the world) was never far from the debate. 

Although in general I’m not a fan of descriptions of ‘data as the new oil’ (I find the equation tends to be made as part of rather breathless techno-deterministic accounts of the future), an extractives metaphor may turn out to be quite useful in asking about the kinds of regulatory regimes that could be appropriate to promote both development, and manage risks, from the rise of data-intensive activity in developing countries.

Over recent decades, principles of extractives governance have developed that recognise the mineral and hydrocarbon resources of a country as at least partially part of the common wealth, such that control of extraction should be regulated, firms involved in extraction should take responsibility for externalities from their work, revenues should be taxed, and taxes invested into development. When we think about firms ‘extracting’ data from a country, perhaps through providing social media platforms and gathering digital trace data, or capturing and processing data from sensor networks, or even collecting genomic information from a biodiverse area to feed into research and product development, what regimes could or should exist to make sure benefits are shared, externalities managed, and the ‘common wealth’ that comes from the collected data, does not entirely flow out of the country, or into the pockets of a small elite?

Although real world extractives governance has often not resolved all these questions successfully, one tool in the governance toolbox has been the  Extractives Industry Transparency Initiative (EITI) . Under EITI, member countries and companies  are required to disclose information on all stages of of the extractives process: from the granting of permissions to operate, through to the taxation or revenue sharing secured, and the social and economic spending that results. The model recognises that governance failures might come from the actions of both companies, and governments – rather than assuming one or the other is the problem or benign. Although transparency alone does not solve governance problems: it can support better debate about both policy design and implementation, and can help address distorting information and power asymmetries that otherwise work against development.

So, what could an analogous initiative look like if applied to international firms involved in ‘data extraction’?

(Note: this is a rough-and-ready thought experiment testing out an extended version of an originally tweet-length thought. It is not a fully developed argument in favour of the ideas explored here).

Data as a national resource

Before conceptualising a ‘data extraction transparency initiative’ we need to first think about what counts as ‘data extraction’.  This involves considering the collected informational (and attention) resources of a population as a whole. Although data itself can be replicated (marking a key difference from finite fossil fuels and mineral resources), the generation and use of data is often rival (i.e. if I spend my time on Facebook, I’m not spending it on some other platform, and/or, some other tasks and activities),  involves first mover advantages (e.g. the first person who street view maps country X may corner the market), and can be made finite through law (e.g. someone collecting genomic material from a country may gain intellectual property rights protection for their data), or simply through restricting access (e.g. as Jeni considers here, where data is gathered from a community and used to shape policy, without the data being shared back to that community).

We could think then of data extraction as any data collection process which ‘uses up’ a common resource such as attention and time, which reduces the competitiveness of a market (thus shifting consumer to producer surplus), or which reduces the potential extent of the knowledge commons through intellectual property regimes or other restrictions on access and use.  Of course, the use of an extracted data resource may have economic and social benefits that feed back to the subjects of the extraction. The point is not that all extraction is bad, but is rather to be aware that data collection and use as an embedded process is definitely not the non-rival, infinitely replicable and zero-cost activity that some economic theories would have us believe.

(Note that underlying this lens is the idea that we should approach data extraction at the level of populations and environments, rather than trying to conceptualise individual ownership of data, and to define extraction in terms of a set of distinct transactions between firms and individuals.)

Past precedent: states and companies

Our model then for data extraction involves a relationship between firms and communities, which we will assume for the moment can be adequately represented by their states. A ‘data extractive transparency initiative’ would then be asking for disclosure from these firms at a country-by-country level, and disclosure from the states themselves. Is this reasonable to expect? 

We can find some precedents for disclosure by looking at the most recent Ranking Digital Rights Report, released last week. This describes how many firms are now providing data about government requests for content or account restriction. A number of companies produce detailed transparency reports that describe content removal requests from government, or show political advertising spend. This at least establishes the idea that voluntarily, or through regulation, it is feasible to expect firms to disclose certain aspects of their operations.

The idea that states should disclose information about their relationship with firms is also reasonably well established (if not wholly widespread). Open Contracting, and the kind of project-level disclosure of payments to government that can be see at ResourceProjects.org illustrate ways in which transparency can be brought to the government-private sector nexus.

In short, encouraging or mandating the kinds of disclosures we might consider below is not a new. Targeted transparency has long been in the regulatory toolbox.

Components of transparency

So – to continue the thought experiment: if we take some of the categories of EITI disclosure, what could this look like in a data context?

Legal framework

Countries would publish in a clear, accessible (and machine-readable?) form, details of the legal frameworks relating to privacy and data protection, intellectual property rights, and taxation of digital industries.

This should help firms to understand their legal obligations in each country, and may also make it easier for smaller firms to provide responsible services across borders without current high costs of finding the basic information needed to make sure they are complying with laws country-by-country.

Firms could also be mandated to make their policies and procedures for data handling clear, accessible (and machine-readable?).

Contracts, licenses and ownership

Whenever governments sign contracts that allow private sector to collect or control data about citizens, public spaces, or the environment, these contracts should be public. 

(In the Data as Development workshop, Sriganesh related the case  of a city that had signed a 20 year deal for broadband provision, signing over all sorts of data to the private firm involved.)

Similarly, licenses to operate, and permissions granted to firms should be clearly and publicly documented.

Recently, EITI has also focussed on beneficial ownership information: seeking to make clear who is really behind companies. For digital industries, mandating clear disclosure of corporate structure, and potentially also of the data-sharing relationships between firms (as GDPR starts to establish) could allow greater scrutiny of who is ultimately benefiting from data extraction.

Production

In the oil, gas and mining context, firms are asked to reveal production volumes (i.e. the amount extracted). The rise of country-by-country reporting, and project-level disclosure has sought to push for information on activity to be revealed not at the aggregated firm level, but in a more granular way.

For data firms, this requirement might translate into disclosure of the quantity of data (in terms of number of users, number of sensors etc.) collected from a country, or disclosure of country by country earnings.

Revenue collection

One important aspect of EITI has been an audit and reconciliation process that checks that the amounts firms claim to be paying in taxes or royalties to government match up with the amounts government claims to have received. This requires disclosure from both private firms and government.

A better understanding of whose digital activities are being taxed, and how, may support design of better policy that allows a share of revenues from data extraction to flow to the populations whose data-related resources are being exploited.

In yesterday’s workshop, Sriganesh pointed to the way in which some developing country governments now treat telecoms firms as an easy tax collection mechanism: if everyone wants a mobile phone connection, and mobile providers are already collecting payments, levying a charge on each connection, or a monthly tax, can be easy to administer. But, in the wrong places, and at the wrong levels, such taxes may capture consumer rather than producer surplus, and suppress rather than support the digital economy,

Perhaps one of the big challenges for ‘data as development’ when companies in more developed economies may extract data from developing countries, but process it back ‘at home’, is that current economic models may suggest that the biggest ‘added value’ is generated from the application of algorithms and processing. This (combined with creative accounting by big firms) can lead to little tax revenue in the countries from which data was originally extracted. Combining ‘production’ and ‘revenue’ data can at least bring this problem into view more clearly – and a strong country-by-country reporting regime may even allow governments to more accurately apply taxes.

Revenue allocation, social and economic spending

Important to the EITI model, is the idea that when governments do tax, or collect royalties, they do so on behalf of the whole polity, and they should be accountable for how they are then using the resulting resources.

By analogy, a ‘data extraction transparency initiative’ initiative may include requirements for greater transparency about how telecoms and data taxes are being used. This could further support multi-stakeholder dialogue on the kinds of public sector investments needed to support national development through use of data resources.

Environmental and social reporting

EITI encourages countries to ‘go beyond the standard and disclose other information too, including environmental information and information on gender.

Similar disclosures could also form part of a ‘data extraction transparency initiative’: encouraging or requiring firms to provide information on gender pay gaps and their environmental impact.

Is implementation possible?

So far this though experiment has established ways of thinking about ‘data extraction’ by analogy to natural resource extraction, and has identified some potential disclosures that could be made by both governments and private actors. It has done so in the context of thinking about sustainable development, and how to protect developing countries from data-exploitation, whilst also supporting them to appropriately and responsibly harness data as a developmental tool. There are some rough edges in all this: but also, I would argue, some quite feasible proposals too (disclosure of data-related contracts for example).

Large scale implementation would, of course, need careful design. The market structure, capital requirements and scale of digital and data firms is quite different to that of the natural resource industry. Compliance costs of any disclosure regime would need to be low enough to ensure that it is not only the biggest firms that can engage. Developing country governments also often have limited capacity when it comes to information management. Yet, most of the disclosures envisaged above relate to transactions that, if ‘born digital’, should be fairly easy to publish data on. And where additional machine-readable data (e.g. on laws and policies) is requested, if standards are designed well, there could be a win-win for firms and governments – for example, by allowing firms to more easily identify and select cloud providers that allow them to comply with the regulatory requirements of a particular country.

The political dimensions of implementation are, of course, another story – and one I’ll leave out of this thought experiment for now.

But why? What could the impact be?

Now we come to the real question. Even if we could create a ‘data extraction transparency initiative’, could it have any meaningful developmental impacts?

Here’s where some of the impacts could lie:

  • If firms had to report more clearly on the amount of ‘data’ they are taking out of a country, and the revenue that gives rise to, governments could tailor licensing and taxation regimes to promote more developmental uses of data. Firms would also be encouraged think about how they are investing in value-generation in countries where they operate. 
  • If contracts that involve data extraction are made public, terms that promote development can be encouraged, and those that diminish the opportunity to national development can be challenged.
  • If a country government chooses to engage in forms of ‘digital protectionism’, or to impose ‘local content requirements’ on the development of data technologies that could bring long-term benefits, but risk creating a short-term hit on the quality of digital services available in a country, greater transparency could support better policy debate. (Noting, however, that recent years have shown us that politics often trumps rational policy making in the real world).

There will inevitably be readers who see the thrust of this thought experiment as fundamentally anti-market, and who are fearful of, or ideologically opposed, to any of the kinds of government intervention that increasing transparency around data extraction might bring. It can be hard to imagine a digital future not dominated by the ever-increased rise of a small number of digital monopolies. But, from a sustainable development point of view, allowing another path to be sought: which supports to creation of resilient domestic technology industries, which prices in positive and negative externalities from data extraction, and which therefore allows active choices to be made about how national data resources are used as common asset, may be no bad thing.

Following the money: preliminary remarks on IATI Traceability

[Summary: Exploring the social and technical dynamics of aid traceability: let’s learn what we can from distributed ledgers, without thinking that all the solutions are to be found in the blockchain.]

My colleagues at Open Data Services are working at the moment on a project for UN Habitat around traceability of aid flows. With an increasing number of organisations publishing data using the International Aid Transparency Initiative data standard, and increasing amounts of government contracting and spending data available online, the theory is that it should be possible to track funding flows.

In this blog post I’ll try and think aloud about some of the opportunities and challenges for traceability.

Why follow funds?

I can envisage a number of hypothetical use cases traceability of aid.

Firstly, donors want to be able to understand where their money has gone. This is important for at least three reasons:

  1. Effectiveness & impact: knowing which projects and programmes have been the most effective;
  2. Understanding and communication: being able to see more information about the projects funded, and to present information on projects and their impacts to the public to build support for development;
  3. Addressing fraud and corruption: identifying leakage and mis-use of funds.

Traceability is important because the relationship between donor and delivery is often indirect. A grant may pass through a number of intermediary organisations before it reaches the ultimately beneficiaries. For example, a country donor may fund a multi-lateral fund, which in turn commissions an international organisation to deliver a programme, and they in turn contract with country partners, who in turn buy in provision from local providers.

Secondly, communities where projects are funded, or where funds should have been receieved, may want to trace funding upwards: understanding the actors and policy agendas affecting their communities, and identifying when funds they are entitled to have not arrived (see the investigative work of Follow The Money Nigeria for a good example of this latter use case).

Short-circuiting social systems

It is important to consider the ways in which work on the traceability of funds potentially bypasses, ‘routes around’ or disrupts* (*choose your own framing) existing funding and reporting relationships – allowing donors or communities to reach beyond intermediaries to exert such authority and power over outcomes as they can exercise.

Take the example given above. We can represent the funding flows in a diagram as below:

downwards

But there are more than one-way-flows going on here. Most of the parties involved will have some sort of reporting responsibility to those giving them funds, and so we also have a report

upwards

By the time reporting gets to the donor, it is unlikely to include much detail on the work of the local partners or providers (indeed, the multilateral, for example, may not report specifically on this project, just on the development co-operation in general). The INGO may even have very limited information about what happens just a few steps down the chain on the ground, having to trust intermediary reports.

In cases where there isn’t complete trust in this network of reporting, and clear mechanisms to ensure each party is excercising it’s responsibility to ensure the most effective, and corruption-free, use of resources by the next party down, the case for being able to see through this chain, tracing funds and having direct ability to assess impacts and risks is clearly desirable.

Yet – it also needs to be approached carefully. Each of the relationships in this funding chain is about more than just passing on some clearly defined packet of money. Each party may bring specific contextual knowledge, skills and experience. Enabling those at the top of a funding chain to leap over intermediaries doesn’t inevitably having a positive impact: particularly given what the history of development co-operative has to teach about how power dynamics and the imposition of top-down solutions can lead to substantial harms.

None of this is a case against traceability – but it is a call for consideration of the social dynamics of traceability infrastructures – and considering of how to ensure contextual knowledge is kept accessible when it becomes possible to traverse the links of a funding chain.

The co-ordination challenge of traceability

Right now, the IATI data standard has support for traceability at the project and transaction level.

  • At the project level the related-activity field can be used to indicate parent, child and co-funded activities.
  • At the transaction level, data on incoming funds can specify the activity-id used by the upstream organisation to identify the project the funds come from, and data on outgoing funds can specify the activity-id used by the downstream organisation.

This supports both upwards and downwards linking (e.g. a funder can publish the identified of the funded project, or a receipient can publish the identifier of the donor project that is providing funds), but is based on explicit co-ordination and the capture of additional data.

As a distributed approach to the publication of open data, there are no consistency checks in IATI to ensure that providers and recipients agree on identifiers, and often there can be practical challenges to capture this data, not least that:

  • A) Many of the accounting systems in which transaction data is captured have no fields for upstream or downstream project identifier, nor any way of conceptually linking transactions to these externally defined projects;
  • B) Some parties in the funding chain may not publish IATI data, or may do so in forms that do not support traceability, breaking the chain;
  • C) The identifier of a downstream project may not be created at the time an upstream project assigns funds – exchanging identifiers can create a substantial administrative burden;

At the last IATI TAG meeting in Ottawa, this led to some discussion of other technologies that might be explored to address issues of traceability.

Technical utopias and practical traceability

Let’s start with a number of assorted observations:

  • UPS can track a package right around the world, giving me regular updates on where it is. The package has a barcode on, and is being transferred by a single company.
  • I can make a faster-payments bank transfer in the UK with a reference number that appears in both my bank statements, and the receipients statements, travelling between banks in seconds. Banks leverage their trust, and use centralised third-party providers as part of data exchange and reconciling funding transfers.
  • When making some international transfers, the money has effectively disappeared from view for quite a while, with lots of time spent on the phone to sender, recipient and intermediary banks to track down the funds. Trust, digital systems and reconciliation services function less well across international borders.
  • Transactions on the BitCoin Blockchain are, to some extent, traceable. BitCoin is a distributed system. (Given any BitCoin ‘address’ it’s possible to go back into the public ledger and see which addresses have transferred an amount of bitcoins there, and to follow the chain onwards. If you can match an address to an identity, the currency, far from being anonymous, is fairly transparent*. This is the reason for BitCoin mixer services, designed to remove the trackability of coins.)
  • There are reported experiments with using BlockChain technologies in a range of different settings, incuding for land registries.
  • There’s a lot of investment going into FinTech right now – exploring ways to update financial services

All of this can lead to some excitement about the potential of new technologies to render funding flows traceable. If we can trace parcels and BitCoins, the argument goes, why can’t we have traceability of public funds and development assistance?

Although I think such an argument falls down in a number of key areas (which I’ll get to in a moment), it does point towards a key component missing from the current aid transparency landscape – in the form of a shared ledger.

One of the reasons IATI is based on a distributed data publishing model, without any internal consistency checks between publishers, is prior experience in the sector of submitting data to centralised aid databases. However, peer-to-peer and block-chain like technologies now offer a way to separate out co-ordination and the creation of consensus on the state of the world, from the centralisation of data in a single database.

It is at least theoretically possible to imagine a world in which the data a government publishes about it’s transactions is only considered part of the story, and in which the recipient needs to confirm receipt in a public ledger to complete the transactional record. Transactions ultimately have two parts (sending and receipt), and open (distributed) ledger systems could offer the ability to layer an auditable record on top of the actual transfer of funds.

However (as I said, there are some serious limitations here), such a system is only an account giving of the funding flows, not the flows themself (unlike BitCoin) which still leaves space for corruption through maintaining false information in the ledger. Although trusted financial intermediaries (banks and others) could be brought into the picture, as others responsible for confirming transactions, it’s hard to envisage how adoption of such a system could be brought about over the short and medium term (particularly globally). Secondly, although transactions between organisations might be made more visible and traceable in this way, the transactions inside an organisation remain opaque. Working out which funds relate to which internal and external projects is still a matter of the internal businesses processes in organisations involved in the aid delivery chain.

There may be other traceability systems we should be exploring as inspirations for aid and public money traceable. What my brief look at BitCoin leads me to reflect on is potential role over the short-term of reconciliation services that can, at the very least, report on the extent to which different IATI publisers are mutually confirming each others information. Over the long-term, a move towards more real-time transparency infrastructures, rather than periodic data publication, might open up new opportunities – although with all sorts of associated challenges.

Ultimately – creating traceable aid still requires labour to generate shared conceptual understandings of how particular transactions and projects relate.

How much is enough?

Let’s loop back round. In this post (as in many of the conversations I’ve had about traceable), we started with some use cases for traceability; we saw some of the challenges; we got briefly excited about what new technologies could do to provide traceability; we saw the opportunities, but also the many limitations. Where do we end up then?

I think important is to loop back to our use cases, and to consider how technology can help but not completely solve, the problems set out. Knowing which provider organisations might have been funded through a particular donors money could be enough to help them target investigations in cases of fraud. Or knowing all the funders who have a stake in projects in a particular country, sector and locality can be enough for communities on the ground to do further research to identify the funders they need to talk to.

Rather than searching after a traceability data panopticon, can we focus traceability-enabling practices on breaking down the barriers to specific investigatory processes?

Ultimately, in the IATI case, getting traceability to work at the project level alone could be a big boost. But doing this will require a lot of social coordination, as much as technical innovation. As we think about tools for traceability, thinking about tools that support this social process may be an important area to focus on.

Where next

Steven Flower and the rest of the Open Data Services team will be working on coming weeks on a deeper investigation of traceability issues – with the goal of producing a report and toolkit later this year. They’ve already been digging into IATI data to look for the links that exist so far and building on past work testing the concept of traceability against real data.

Drop in comments below, or drop Steven a line, if you have ideas to share.

Data, openness, community ownership and the commons

[Summary: reflections on responses to the GODAN discussion paper on agricultural open data, ownership and the commons – posted ahead of Africa Open Data Conference GODAN sessions]

Photo Credit - CC-BY - South Africa Tourism
]3 Photo Credit – CC-BY – South Africa Tourism

Key points

  • We need to distinguish between claims to data ownership, and claims to be a stakeholder in a dataset;
  • Ownership is a relevant concept for a limited range of datasets;
  • Openness can be a positive strategy, empowering farmers vis-a-vis large corporate interests;
  • Openness is not universally good: can also be used as a ‘data grab’ strategy;
  • We need to think critically about the configurations of openness we are promoting;
  • Commons and cooperative based strategies for managing data and open data are a key area for further exploration;

Open or owned data?

Following the publication of a discussion paper by the ODI for the Global Open Data for Agriculture and Nutrition initiative, putting forward a case for how open data can help improve agriculture, food and nutrition, debate has been growing about how open data should be approached in the context of smallholder agriculture. In this post, I explore some provisional reflections on that debate.

Respondents to the paper have pointed to the way in which, in situations of unequal power, and in complex global markets, greater accessibility of data can have substantial downsides for farmers. For example, commodity speculation based on open weather data can drive up food prices, or open data on soil profiles can be used in order to extract greater margins from farmers when selling fertilizers. A number of responses to the ODI paper have noted that much of the information that feeds into emerging models of data-driven agriculture is coming from small-scale farmers themselves: whether through statistical collection by governments, or hoovered up by providers of farming technology, all aggregated into big datasets that practically inaccessible to local communities and farmers.

This has led to some focussing in response on the concept of data ownership: asserting that more emphasis should be placed on community ownership of the data generated at a local level. Equally, it has led to the argument that “opening data without enabling effective, equitable use can be considered a form of piracy”, making direct allusions to the biopiracy debate and the consequent responses to such concerns in the form of interventions such as the International Treaty on Plant Genetic Resources.

There are valid concerns here. Efforts to open up data must be interrogated to understand which actors stand to benefit, and to identify whether the configuration of openness sought is one that will promote the outcomes claimed. However, claims of data ownership and data sovereignty need to be taken as a starting point for designing better configurations of openness, rather than as a blocking counter-claim to ideas of open data.

Community ownership and openness

My thinking on this topic is shaped, albeit not to a set conclusion, by a debate that took place last year at a Berkman Centre Fellows Hour based on a presentation by Pushpa Kumar Lakshmanan on the Nagoya Protocol which sets out a framework for community ownership and control over genetic resources.

The debate raised the tension between the rights of communities to gain benefits from the resources and knowledge that they have stewarded, potentially over centuries, with an open knowledge approach that argues social progress is better served when knowledge is freely shared.

It also raised important questions of how communities can be demarcated (a long-standing and challenging issue in the philosophy of community rights) – and whether drawing a boundary to protect a community from external exploitation risks leaving internal patterns of power and exploitation within the community unexplored. For example, does community ownership of data really lead to certain elites in the community controlling it.

Ultimately, the debate taps into a conflict between those who see the greatest risk as being the exploitation of local communities by powerful economic actors, and those who see the greater risk as a conservative hoarding of knowledge in local communities in ways that inhibit important collective progress.

Exploring ownership claims

It is useful to note that much of the work on the Nagoya Protocol that Pushpa described was centred on controlling borders to regulate the physical transfer of plant genetic material. Thinking about rights over intangible data raises a whole new set of issues: ownership cannot just be filtered through a lens of possession and physical control.

Much data is relational. That is to say that it represents a relationship between two parties, or represents objects that may stand in ownership relationships with different parties. For example, in his response to the GODAN paper, Ajit Maru reports how “John Deere now considers its tractors and other equipment as legally ‘software’ and not a machine… [and] claims [this] gives them the right to use data generated as ‘feedback’ from their machinery”. Yet, this data about a tractor’s operation is also data about the farmers land, crops and work. The same kinds of ‘trade data for service’ concerns that have long been discussed with reference to social media websites are becoming an increasing part of the agriculture world. The concern here is with a kind of corporate data-grab, in which firms extract data, asserting their absolute ownership over something which is primarily generated by the farmer, and which is at best a co-production of farmer and firm.

It is in response to this kind of situation that grassroots data ownership claims are made.

These ownership claims can vary in strength. For example:

  • The farmer can claim that ‘this is my data’, and I should have ultimate control over how it is used, and the ability to treat it as a personally held asset;

  • The second runs that ‘I have a stake in this data’, and as a consequence, I should have access to it, and a say in how it is used;

Which claim is relevant depends very much on the nature of the data. For example, we might allow ownership claims over data about the self (personal data), and the direct property of an individual. For datasets that are more clearly relational, or collectively owned (for example, local statistics collected by agricultural extension workers, or weather data funded by taxation), the stakeholding claim is the more relevant.

It is important at this point to note that not all (perhaps even not many) concerns about the potential misuse of data can be dealt with effectively through a property right regime. Uses of data to abuse privacy, or to speculate and manipulate markets may be much better dealt with by regulations and prohibitions on those activities, rather than attempts to restrict the flow of data through assertions of data ownership.

Openness as a strategy

Once we know whether we are dealing with ownership claims, or stakeholding claims, in data, we can start thinking about different strategic configurations of openness, that take into account power relationships, and that seek to balance protection against exploitation, with the benefits that can come from collaboration and sharing.

For example, each farmer on their own has limited power vis-a-vis a high-tech tractor maker like John Deere. Even if they can assert a right to access their own data, John Deere will most likely retain the power to aggregate data from 1000s of farmers, maintaining an inequality of access to data vis-a-vis the farmer. If the farmer seeks to deny John Deere the right to aggregate their data with that of others: changes that (a) they will be unsuccessful, as making an absolute ownership claim here is difficult – using the tractor was a choice after all; and (b) they will potentially inhibit useful research and use of data that could improve cropping (even if some of the other uses of the data may run counter to the farmers interest). Some have suggested that creating a market in the data, where the data aggregator would pay the farmers for the ability to use their data, offers an alternative path here: but it is not clear that the price would compensate the farmer adequately, or lead to an efficient re-use of data.

However, in this setting openness potentially offers an alternative strategy. If farmers argue that they will only give data to John Deere if John Deere makes the aggregated data open, then they have the chance to challenge the asymmetry of power that otherwise develops. A range of actors and intermediaries can then use this data to provide services in the interests of the farmers. Both the technology provider, and the farmer, get access to the data in which they are both stakeholders.

This strategy (“I’ll give you data only if you make the aggregate set of data you gather open”), may require collective action from farmers. This may be the kind of arrangement GODAN can play a role in brokering, particularly as it may also turn out to be in the interest of the firm as well. Information economics has demonstrated how firms often under-share information which, if open, could lead to an expansion of the overall market and better equilibria in which, rather than a zero-sum game, there are benefits to be shared amongst market actors.

There will, however, be cases in which the power imbalances between data providers and those who could exploit the data are too large. For example, the above discussion assumes intermediaries will emerge who can help make effective use of aggregated data in the interests of farmers. Sometimes (a) the greatest use will need to be based on analysis of disaggregated data, which cannot be released openly; and (b) data providers need to find ways to work together to make use of data. In these cases, there may be a lot to learn from the history of commons and co-operative structures in the agricultural realm.

Co-operative and commons based strategies

Many discussions of openness conflate the concept of openness, and the concept of the commons. Yet there is an important distinction. Put crudely:

  • Open = anyone is free to use/re-use a resource;
  • Commons = mutual rights and responsibilities towards the resource;

In the context of digital works, Creative Commons provide a suite of licenses for content, some of which are ‘open’ (they place no responsibilities on users of a resource, but grant broad rights), and others of which adopt a more regulated commons approach, placing certain obligations on re-users of a document, photo or dataset, such as the responsibility to attribute the source, and share any derivative work under the same terms.

The Creative Commons draws upon an imagery from the physical commons. These commons were often in the form of land over which farmers held certain rights to graze cattle, of fisheries in which each fisher took shared responsibility for avoiding overfishing. Such commons are, in practice, highly regulated spaces – but that seek to pursue an approach based on sharing and stakeholding in resources, rather than absolute ownership claims. As we think about data resources in agriculture, reflecting more on learning from the commons is likely to prove fruitful. Of course, data, unlike land, is not finite in the same ways, nor does it have the same properties of excludability and rivalrousness.

In thinking about how to manage data commons, we might look towards another feature prevalent in agricultural production: that of the cooperative. The core idea of a data cooperative is that data can be held in trust by a body collectively owned by those who contribute the data. Such data cooperatives could help manage the boundary between data that is made open at some suitable level of aggregation, and data that is analysed and used to generate products of use to those contributing the data.

With Open Data Services Co-operative I’ve just started to dig more into learning about the cooperative movement: co-founding a workers cooperative that supports open data projects. However, we’ve also been thinking about how data cooperatives might work – and I’m certain there is scope for a lot more work in this area, helping deal with some of the critical questions that have come up for open data from the GODAN discussion paper.

Creating the capacity building game…

Open Development Camp Logo[Summary: crowdsourcing contributions to a workshop at Open Development Camp]

There is a lot of talk of ‘capacity building’ in the open data world. As the first phase of the ODDC project found, there are many gaps between the potential of open data and it’s realisation: and many of these gaps can be described as capacity gaps – whether on the side of data suppliers, or potential data users.

But how does sustainable capacity for working with open data develop? At the Open Development Camp in a few weeks time I’ll be facilitating a workshop to explore this question, and to support participants to share learning about how different capacity building approaches fit in different settings.

The basic idea is that we’ll use a simple ‘cards and scenarios’ game (modelled, as ever, on the Social Media Game), where we identify a set of scenarios with capacity building needs, and then work in teams to design responses, based on combining a selection of different approaches, each of which will be listed one of the game cards.

But, rather than just work from the cards, I’m hoping that for many of these approaches there will be ‘champions’ on hand, able to make the case for that particular approach, and to provide expert insights to the team. So:

  • (1) I’ve put together a list of 24+ different capacity building approaches I’ve seen in the open data world – but I need your help to fill in the details of their strengths, weaknesses and examples of them in action.
  • (2) I’m looking for ‘champions’ for these approaches, either who will be at the Open Development Camp, or who could prepare a short video input in advance to make the case for their preferred capacity building approach;

If you could help with either, get in touch, or dive in direct on this Google Doc.

If all goes well, I’ll prepare a toolkit after the Open Development Camp for anyone to run their own version of the Capacity Building Game.

The list so far

Click each one to jump direct to the draft document

Fifteen open data insights

ODDC Phase 1 Report - Cover[Summary: blogging the three-page version of Open Data in Developing Countries – Emerging Insights from Phase I paper, with some preamble]

I’m back living in Oxford after my almost-year in the USA at the Berkman Center. Before we returned, Rachel and I took a month to travel around the US – by Amtrak. The delightfully ponderous pace of US trains gave me plenty of time for reading, which was just as well, given June was the month when most of the partners in the Open Data in Developing Countries project I coordinate were producing their final reports. So, in-between time staring at the stunning scenery as we climbed through the Rockies, or watching amazing lightening storms from the viewing car, I was digging through in-depth reports into open data in the global south, and trying to pick out common themes and issues. A combination of post-it notes and scrivener index cards later, and finally back at my desk in Oxford, the result was a report, released alongside the ODDC Research Sharing Event in Berlin last week, that seeks to snapshot 15 insights or provocations for policy-makers and practitioners drawn out from the ODDC case study reports.

These are just the first stage of the synthesis work to be carried out in the ODDC project. In the network meeting also hosted in Berlin last week, we worked on mapping these and other findings from projects onto the original conceptual framework of the project, and looked at identifying further cross-cutting write-ups required. But, for now, below are the 15 points from the three-page briefing version, and you can find a full write-up of these points for download. You can also find reports from all the individual project partners, including a collection of quick-read research posters over on the Open Data Research Network website.

15 insights into open data supply, use and impacts

(1) There are many gaps to overcome before open data availability, can lead to widespread effective use and impact. Open data can lead to change through a ‘domino effect’, or by creating ripples of change that gradually spread out. However, often many of the key ‘domino pieces’ are missing, and local political contexts limit the reach of ripples. Poor data quality, low connectivity, scarce technical skills, weak legal frameworks and political barriers may all prevent open data triggering sustainable change. Attentiveness to all the components of open data impact is needed when designing interventions.

(2) There is a frequent mismatch between open data supply and demand in developing countries. Counting datasets is a poor way of assessing the quality of an open data initiative. The datasets published on portals are often the datasets that are easiest to publish, not the datasets most in demand. Politically sensitive datasets are particularly unlikely to be published without civil society pressure. Sometimes the gap is on the demand side – as potential open data users often do not articulate demands for key datasets.

(3) Open data initiatives can create new spaces for civil society to pursue government accountability and effectiveness. The conversation around transparency and accountability that ideas of open data can support is as important as the datasets in some developing countries.

(4) Working on open data projects can change how government creates, prepares and uses its own data. The motivations behind an open data initiative shape how government uses the data itself. Civil society and entrepreneurs interacting with government through open data projects can help shape government data practices. This makes it important to consider which intermediaries gain insider roles shaping data supply.

(5) Intermediaries are vital to both the supply and the use of open data. Not all data needed for governance in developing countries comes from government. Intermediaries can create data, articulate demands for data, and help translate open data visions from political leaders into effective implementations. Traditional local intermediaries are an important source of information, in particular because they are trusted parties.

(6) Digital divides create data divides in both the supply and use of data. In some developing countries key data is not digitised, or a lack of technical staff has left data management patchy and inconsistent. Where Internet access is scarce, few citizens can have direct access to data or services built with it. Full access is needed for full empowerment, but offline intermediaries, including journalists and community radio stations, also play a vital role in bridging the gaps between data and citizens.

(7) Where information is already available and used, the shift to open data involves data evolution rather than data revolution. Many NGOs and intermediaries already access the information which is now becoming available as data. Capacity building should start from existing information and data practices in organisations, and should look for the step-by-step gains to be made from a data-driven approach.

(8) Officials’ fears about the integrity of data are a barrier to more machine-readable data being made available. The publication of data as PDF or in scanned copies is often down to a misunderstanding of how open data works. Only copies can be changed, and originals can be kept authoritative. Helping officials understand this may help increase the supply of data.

(9) Very few datasets are clearly openly licensed, and there is low understanding of what open licenses entail. There are mixed opinions on the importance of a focus on licensing in different contexts. Clear licenses are important to building a global commons of interoperable data, but may be less relevant to particular uses of data on the ground. In many countries wider conversation about licensing are yet to take place.

(10) Privacy issues are not on the radar of most developing country open data projects, although commercial confidentiality does arise as a reason preventing greater data transparency. Much state held data is collected either from citizens or from companies. Few countries in the ODDC study have weak or absent privacy laws and frameworks, yet participants in the studies raised few personal privacy considerations. By contrast, a lack of clarity, and officials’ concerns, about potential breaches of commercial confidentiality when sharing data gathered from firms was a barrier to opening data.

(11) There is more to open data than policies and portals. Whilst central open data portals act as a visible symbol of open data initiatives, a focus on portal building can distract attention from wider reforms. Open data elements can also be built on existing data sharing practices, and data made available through the locations where citizens, NGOs are businesses already go to access information.

(12) Open data advocacy should be aware of, and build upon, existing policy foundations in specific countries and sectors. Sectoral transparency policies for local government, budget and energy industry regulation, amongst others, could all have open data requirements and standards attached, drawing on existing mechanisms to secure sustainable supplies of relevant open data in developing countries. In addition, open data conversations could help make existing data collection and disclosure requirements fit better with the information and data demands of citizens.

(13) Open data is not just a central government issue: local government data, city data, and data from the judicial and legislative branches are all important. Many open data projects focus on the national level, and only on the executive branch. However, local government is closer to citizens, urban areas bring together many of the key ingredients for successful open data initiatives, and transparency in other branches of government is important to secure citizens democratic rights.

(14) Flexibility is needed in the application of definitions of open data to allow locally relevant and effective open data debates and advocacy to emerge. Open data is made up of various elements, including proactive publication, machine-readability and permissions to re-use. Countries at different stages of open data development may choose to focus on one or more of these, but recognising that adopting all elements at once could hinder progress. It is important to find ways to both define open data clearly, and to avoid a reductive debate that does not recognise progressive steps towards greater openness.

(15) There are many different models for an open data initiative: including top-down, bottom-up and sector-specific. Initiatives may also be state-led, civil society-led and entrepreneur-led in their goals and how they are implemented – with consequences for the resources and models required to make them sustainable. There is no one-size-fits-all approach to open data. More experimentation, evaluation and shared learning on the components, partners and processes for putting open data ideas into practice must be a priority for all who want to see a world where open-by-default data drives real social, political and economic change.

You can read more about each of these points in the full report.

New Paper – Mixed incentives: Adopting ICT innovations for transparency, accountability, and anti-corruption

7353-U4Issue-2014-03-04-WEB

[Summary: critical questions to ask when planning, funding or working on ICTs for transparency and accountability]

Last year I posted some drafts of a paper I’ve been writing with Silvana Fumega at the invitation of the U4 Anti-Corruption Center, looking at the incentives for, and dynamics of, adoption of ICTs as anti-corruption tools. Last week the final paper was published in the U4 Issue series, and you can find it for download here.

In the final iteration of the paper we have sought to capture the core of the analysis in the form of a series of critical questions that funders, planners and implementers of anti-corruption ICTs can ask. These are included in the executive summary below, and elaborated more in the full paper.

Adopting ICT innovations for transparency, accountability, and anti-corruption – Executive Summary

Initiatives facilitated by information and communication technology (ICT) are playing an increasingly central role in discourses of transparency, accountability, and anti-corruption. Both advocacy and funding are being mobilised to encourage governments to adopt new technologies aimed at combating corruption. Advocates and funders need to ask critical questions about how innovations from one setting might be transferred to another, assessing how ICTs affect the flow of information, how incentives for their adoption shape implementation, and how citizen engagement and the local context affect the potential impacts of their use.

ICTs can be applied to anti-corruption efforts in many different ways. These technologies change the flow of information between governments and citizens, as well as between different actors within governments and within civil society. E?government ICTs often seek to address corruption by automating processes and restricting discretion of officials. However, many contemporary uses of ICTs place more emphasis on the concept of transparency as a key mechanism to address corruption. Here, a distinction can be made between technologies that support “upward transparency,” where the state gains greater ability to observe and hear from its citizens, or higher-up actors in the state gain greater ability to observe their subordinates, and “downward transparency,” in which “the ‘ruled’ can observe the conduct, behaviour, and/or ‘results’ of their ‘rulers’” (Heald 2006). Streamlined systems that citizens can use to report issues to government fall into the former category, while transparency portals and open data portals are examples of the latter. Transparency alone can only be a starting point for addressing corruption, however: change requires individuals, groups, and institutions who can access and respond to the information.

In any particular application of technology with anti-corruption potential, it is important to ask:

  • What is the direction of the information flow: from whom and to whom?
  • Who controls the flow of information, and at what stages?
  • Who needs to act on the information in order to address corruption?

Different incentives can drive government adoption of ICTs. The current wave of interest in ICT for anti-corruption is relatively new, and limited evidence exists to quantify the benefits that particular technologies can bring in a given context. However, this is not limiting enthusiasm for the idea that governments, particularly developing country governments, can adopt new technologies as part of open government and anti-corruption efforts. Many technologies are “sold” on the basis of multiple promised benefits, and governments respond to a range of different incentives. For example, governments may use ICTs to:

  • Improve information flow and government efficiency, creating more responsive public institutions, supporting coordination.
  • Provide open access to data to enable innovation and economic growth, responding to claims about the economic value of open data and its role as a resource for private enterprise.
  • Address principal-agent problems, allowing progressive and reformist actors within the state to better manage and regulate other parts of the state by detecting and addressing corruption through upward and downward transparency.
  • Respond to international pressure, following the trends in global conversations and pressure from donors and businesses, as well as the availability of funding for pilots and projects.
  • Respond to bottom-up pressure, both from established civil society and from an emerging global network of technology-focussed civil society actors. Governments may do this either as genuine engagement or to “domesticate” what might otherwise be seen as disruptive innovations.

In supporting ICTs for anti-corruption, advocates and donors should consider several key questions related to incentives:

  • What are the stated motivations of government for engaging with this ICT?
  • What other incentives and motivations may be underlying interest in this ICT?
  • Which incentives are strongest? Are any of the incentives in conflict?
  • Which incentives are important to securing anti-corruption outcomes from this ICT?
  • Who may be motivated to oppose or inhibit the anti-corruption applications of this ICT?

The impact of ICTs for anti-corruption is shaped by citizen engagement in a local context. Whether aimed at upward or downward transparency, the successful anti-corruption application of an ICT relies upon citizen engagement. Many factors affect which citizens can engage through technology to share reports with government or act upon information provided by government. ICTs that worked in one context might not achieve the same results in a different setting (McGee and Gaventa 2010). The following questions draw attention to key aspects of context:

  • Who has access to the relevant technologies? What barriers of connectivity, literacy, language, or culture might prevent a certain part of the population from engaging with an ICT innovation?
  • What alternative channels (SMS, offline outreach) might be required to increase the reach of this innovation?
  • How will the initiative close the feedback loop? Will citizens see visible outcomes over the short or long term that build rather than undermine trust?
  • Who are the potential intermediary groups and centralised users for ICTs that provide upward or downward transparency? Are both technical and social intermediaries present? Are they able to work together?

Towards sustainable and effective anti-corruption use of ICTs. As Strand (2010) argues, “While ICT is not a magic bullet when it comes to ensuring greater transparency and less corruption . . . it has a significant role to play as a tool in a number of important areas.” Although taking advantage of the multiple potential benefits of open data, transparency portals, or digitised communication with government can make it easier to start a project, funders and advocates should consider the incentives for ICT adoption and their likely impact on how the technology will be applied in practice. Each of the questions above is important to understanding the role a particular technology might play and the factors that affect how it is implemented and utilised in a particular country.

 

You can read the full paper here.

ODDC Update at Developers for Development, Montreal

[Summary: Cross posted from the Open Data Research Network website. Notes from a talk at OD4DC Montreal] 

I’m in Montreal this week for the Developers for Development hackathon and conference. Asides from having fun building a few things as part of our first explorations for the Open Contracting Data Standard, I was also on a panel with the fantastic Linda Raftree, Laurent Elder and Anahi Ayala Iacucci focussing on the topic of open data impacts in developing country: a topic I spend a lot of time working on. We’re still in the research phase of the Emerging Impacts of Open Data in Developing Countries research network, but I tried to pull together a talk that would capture some of the themes that have been coming up in our network meetings so far. So – herewith the slides and raw notes from that talk.

Introduction

In this short presentation I want to focus on three things. Firstly, I want to present a global snapshot of open data readiness, implementation and impacts around the world.

Secondly, I want to offer some remarks on the importance of how research into open data is framed, and what social research can bring to our understanding of the open data landscape in developing countries.

Lastly, I want to share a number of critical reflections emerging from the work of the ODDC network.

Part 1: A global snapshot

I’ve often started presentations and papers about open data by commenting on how ‘it’s just a few short years since the idea of open data gained traction’, yet, in 2014 that line is starting to get a little old. Data.gov launched in 2009, Kenya’s data portal in 2011. IATI has been with us for a while. Open data is no longer a brand new idea, just waiting to be embraced – it is becoming part of the mainstream discourse of development and government policy. The issue now is less about convincing governments to engage with the open data agenda, than it is about discovering whether open data discourses are translating into effective implementation, and ultimately open data impacts.

Back in June last year, at the Web Foundation we launched a global expert survey to help address that question. All-in-all we collected data covering 77 countries, representing every region, type of government and level of development, and asking about government, civil society and business readiness to secure benefits from open data, the actual availability of key datasets, and observed impacts from open data. The results were striking: over 55% of these diverse countries surveyed had some form of open data policy in place, many with high-level ministerial support.

The policy picture looks good. Yet, when it came to key datasets actually being made available as open data, the picture was very different. Less than 7% of the dataset surveyed in the Barometer were published both in bulk machine-readable forms, and under open licenses: that is, in ways that would meet the open definition. And much of this percentage is made up of the datasets published by a few leading developed states. When it comes to essential infrastructural datasets like national maps, company registers or land registries, data availability, of even non-open data, is very poor, and particularly bad in developing countries. In many countries, the kinds of cadastral records that are cited as a key to the economic potential of open data are simple not yet collected with full country coverage. Many countries have long-standing capacity building programs to help them create land registries or detailed national maps – but with many such programmes years or even decades behind on delivering the required datasets.

The one exception where data was generally available and well curated, albeit not provided in open and accessible forms, was census data. National statistics offices have been the beneficiaries of years of capacity building support: yet the same programmes that have enabled them to manage data well have also helped them to become quasi-independent of governments, complicating whether or not they will easily be covered by government open data policies.

If the implementation story is disappointing, the impact story is even more so. In the Barometer survey we asked expert researchers to cite examples of where open data was reported in the media, or in academic sources, to have had impacts across a range of political, social and economic domains, and to score questions on a 10-point scale for the breadth and depth of impacts identified. The scores were universally low. Of course, whilst the idea of open data can no longer be claimed to be brand new, many country open data initiatives are – and so it is far to day that outcomes and impacts take time – and are unlikely to be seen over in any substantial way over the very short term. Yet, even in countries where open data has been present for a number of years, evidence of impact was light. The impacts cited were often hackathon applications, which, important as they are, generally only prototype and point to potential impacts. Without getting to scale, few demo applications along can deliver substantial change.

Of course, some of this impact evidence gap may also be down to weaknesses in existing research. Some of the outcomes from open data publication are not easily picked up in visible applications or high profile news stories. That’s where the need for a qualitative research agenda really comes in.

Part 2: The Open Data Barometer

The Open Data Barometer is just one part of a wider open data programme at the World Wide Web Foundation, including the Open Data in Development Countries research project supported by Canada’s International Development Research Center. The main focus of that project over the last 12 months has been on establishing a network of case study research partners based in developing countries, each responding to both local concerns, and a shared research agenda, to understand how open data can be put to use in particular decision making and governance situations.

Our case study partners are drawn from Universities, NGOs and independent consultancies, and were selected from responses to an open call for proposals issues in mid 2012. Interestingly, many of these partners were not open data experts, or already involved in open data – but were focussed on particular social and policy issues, and were interested in looking at what open data meant for these. Focus areas for the cases range from budget and aid transparency, to higher education performance, to the location of sanitation facilities in a city. Together, these foundations gives the research network a number of important characteristics:

Firstly, whilst we have a shared research framework that highlights particular elements that each case study seeks to incorporate – from looking at the political, social and economic context of open data, through to the technical features of datasets and the actions of intermediaries – cases are also able to look at the different constraints exogenous to datasets themselves which affect whether or not data has a chance of making a difference.

Secondly, the research network works to build critical research capacity around open data – bringing new voices into the open data debate. For example, in Kenya, the Jesuit Hakimani Trust have an established record working on citizens access to information, but until 2013 had not looking at the issue of open data in Kenya. By incorporating questions about open data in their large-scale surveys of citizen attitudes, they start generating evidence that treats open data alongside other forms of access to information for poor and marginalisd citizens, generating new insights.

Thirdly, the research is open to unintended consequences of open data publication: good and bad – and can look for impacts outside the classic logic model of ‘data + apps = impact’. Indeed, as researchers in both Sao Paulo and Chennai have found, they have, as respected research intermediaries exploring open data use, been invited to get involved with shaping future government data collection practices. Gisele Craviero from the University of Sao Paulo uses the metaphor of an iceberg to highlight this importance of looking below the surface. The idea that opening data ultimately changes what data gets collected, and how it is handled inside the state should not be an alien idea for those involved in IATI – which has led to many aid agencies starting to geocode their data. But it is a route to effects often underplayed in explorations of the changes open data may be part of bringing about.

Part 3: Emerging findings

As mentioned, we’ve spent much of 2013 building up the Open Data in Developing Countries research network – and our case study parters are right now in the midst of their data collection and analysis. We’re looking forward to presenting full findings from this first phase of research towards the summer, but there are some emerging themes that I’ve been hearing from the network in my role as coordinator that I want to draw out. I should note that these points of analysis are preliminary, and are the product of conversations within the network, rather than being final statements, or points that I claim specific authorship over.

We need to unpack the definition of open data.

Open data is generally presented as a package with a formal definition. Open data is data that is proactively published, in machine-readable formats, and under open licenses. Without all of these: there isn’t open data. Yet, ODDC participants have been highlighting how the relative importance of these criteria varies from country to country. In Sierra Leone, for example, machine-readable formats might be argued to be less important right now than proactive publication, as for many datasets the authoritative copy may well be the copy on paper. In India, Nigeria or Brazil, the question of licensing may by mute: as it is either assumed that government data is free to re-use, regardless or explicit statements, or local data re-users may be unconcerned with violating licenses, based on a rational expectation that no-one will come after them.

Now – this is not to say that the Open Definition should be abandoned, but we should be critically aware of it’s primary strength: it helps to create a global open data commons, and to deliver on a vision of ‘Frictionless data’. Open data of this form is easier to access ‘top down’, and can more easily be incorporated into panopticon-like development dashboards, but the actual impact on ‘bottom up’ re-use may be minimal. Unless actors in a developing country are equipped with the skills and capacities to draw on this global commons, and to overcome other local ‘frictions’ to re-using data effectively, the direct ROI on the extra effort to meet a pure open definition might not accrue to those putting the effort in: and a dogmatic focus on strict definitions might even in some cases slow down the process of making data relatively more accessible. Understanding the trade offs here requires more research and analysis – but the point at least is made that there can be differences of emphasis in opening data, and these prioritise different potential users.

Supply is weak, but so is demand.

Talking at the Philippines Good Governance Summit a few weeks ago, Michael Canares presented findings from his research into how the local government Full Disclosure Policy (FDP) is affecting both ‘duty bearers’ responsible for supplying information on local budgets, projects, spend and so-on, and ‘claim holders’ – citizens and their associations who seek to secure good services from government. A major finding has been that, with publishers being in ‘compliance mode’, putting required information but in accessible formats, citizen groups articulated very little demand for online access to Full Disclosure Policy information. Awareness that the information was available was low, interest in the particular data published was low (that is, information made available did not match with any specific demand), and where citizen groups were accessing the data they often found they did not have the knowledge to make sense of or use it. The most viewed and download documents garnered no more than 43 visits in the period surveyed.

In open data, as we remove the formal or technical barriers to data re-use that come from licenses and non-standard formats, we encounter the informal hurdles, roadblocks and thickets that lay behind them. And even as those new barriers are removed through capacity building and intermediation, we may find that they were not necessarily holding back a tide of latent demand – but were rather theoretical barriers in the way of a progressive vision of an engaged citizenry and innovative public service provision. Beyond simply calling for the removal of barriers, this vision needs to be elaborated – whether through the designs of civic leaders, or through the distributed actions of a broad range of social activists and entrepreneurs. And the tricky challenge of culture change – changing expectations of who is, and can be, empowered – needs to be brought to the fore.

Innovative intermediation is about more than visualisation.

Early open data portals listed datasets. Then they started listing third party apps. Now, many profile interactive visualisations built with data, or provide visualisation tools. Apps and infographics have become the main thing people think of when it comes to ‘intermediaries’ making open data accessible. Yet, if you look at how information flows on the ground in developing countries, mobile messaging, community radio, notice boards, churches and chiefs centres are much more likely to come up as key sites of engagement with public information.

What might open data capacity building look like if we started with these intermediaries, and only brought technology in to improve the flow of data where that was needed? What does data need to be shaped like to enable these intermediaries to act with it? And how do the interests of these intermediaries, and the constituencies they serve, affect what will happen with open data? All these are questions we need to dig into further.

Summary

I said in the opening that this would be a presentation of critical reflections. It is important to emphasise that none of this constitutes an argument against open data. The idea that government data should be accessible to citizens retains its strong intrinsic appeal. Rather, in offering some critical remarks, I hope this can help us to consider different directions open data for development can take as it matures, and that ultimately we can move more firmly towards securing impacts from the important open data efforts so many parties are undertaking.

ICTs and Anti-Corruption: Uptake, use and impacts

[Summary: The forth section of our draft paper on ICTs and Anti-corruption looks at the evidence on uptake, use and impacts. We’d love your comments…

I’m currently posting draft sections of a report on ICTs and anti-corruption to invite comments before the final paper is written up in a few weeks time. If you’ve any comments on the draft, please do add them into the Google Doc draft or leave a note below. This forth and final section looks at uptake of anti-corruption ICTs in developing country contexts and issues concerning who uses these technologies.

4. UPTAKE, USE AND IMPACTS

Government incentives aside, it is important for advocates and funders of ICT-enabled anti-corruption activity to consider the factors that may affect the impact of these interventions in developing countries. As previously outlined, ICT-based reforms tend to focus on either transactions or transparency. Both rely upon the engagement of citizens. Citizens are crucial either to access and respond to information that is made available through transparency, or to originate and communicate to government their own experience through transactional channels. Therefore, it is important to ask what incentives and barriers citizens have for such engagement, and to explore what kinds of citizen engagement are important to the success of certain ICTs.

 

4.1 THE CITIZEN ROLE

Much of the limited evidence we do have on citizen engagement with transparency and accountability ICTs comes from cases where those tools/platforms have been deployed by civil society. Avila et. al. divide interventions into two kinds: push and pull transparency (Avila, Feigenblatt, Heacock, & Heller, 2011). In the former, citizens speak up, and communicate their experience of an issue; in the later, citizens ‘pull’ down information from an available pool and use it to act in some way. In practice, many interventions require both: citizens to access information, and citizens to act through exercising their voice and pushing issues onto the agenda (Avila, R. et al, 2009). An ICT intervention might be designed around the idea of citizens acting individually (e.g. in transactional citizen reporting channels), or around the idea of citizens acting collectively, as in the idea of that, on identifying corrupt activity through information on a transparency portal, or an open data catalogue, citizens speak out politically on the need for change. Citizen action in these cases may be direct, or mediated. In mediated cases, technical intermediaries, sometimes termed “infomediaries”, play a particularly important role in theories of change around how open data may be used by citizens (Steinberg, 2011).

 

4.2 WHICH CITIZENS?

The effort, as well as the skills, that each of these different models (push or pull; individual or collective action) demand from the citizens varies significantly across ICT interventions. Users can be passive consumers of information, accumulating it to use at some future point, such as when voting. Or, as Fung et al (2010) outline, they can be requested to act on information that they receive, drawing on a range of resources to make a change in their behaviour as a result of transparent information, for example in citizens’ reporting channel (from government or civil society) or in participatory budget exercises.

 

Differences emerge not only between the users of different models, also amongst users in each of them. The skills, resources and capacity to influence others are not the same between mass users (general public) and organized entities (such as NGOs, journalist, companies and public officials). According to Fung et. al. (2011) the interventions that aim to increase political accountability (understood as the demand over the “behaviour of political officials whose policies have more generalized effects”) generally rely upon centralized users (media, NGOs, among others) while the general public (decentralized actors) tend to be more inclined towards interventions designed to demand service accountability (ibid.). This distinction seems to present some sort of correlation with the assumption that people values information that is directly relevant to their well-being and they are interested in a few select political issues that are directly relevant to their lives.

 

Besides the incentives behind each user, there certainly is a disparity in terms of resources to disseminate the information and also regarding the capacity to channel demands through the appropriate institutional channels. Following Fung et. al. “political campaigns and candidates, for example, may be far more sensitive and responsive to the criticisms that journalists make than to the more diffuse, harder to discern views of mass voters” (Fung et al., 2011).

 

In terms of the characteristics of the mass users, there is limited analysis on the demographics of ICT-led transparency initiatives user. Some reports argue that poorer demographics are the most affected by corruption (Knox, 2009). Despite that, the analysis that does exist suggests that more educated, higher income and more technologically comfortable demographics of the population are more incline to engage with ICT-led interventions (Kuriyan, Bailur, Gigler, & Park, 2012). It is perhaps not surprising as these groups are the most likely to be online and to engage with Internet applications more frequently, as well as more likely to participate in politics. However, the implications of this for the design of technology for anti-corruption projects is offer an afterthought, rather than a key design consideration from the start. The fact that ICT-based innovations may primarily reach relatively predictable (and relatively affluent) proportions of the population (at least in the short term) may play a role in making such approaches appealing to governments who believe they can manage any input they may receive within existing institutional processes.

 

4.3 BARRIERS TO UPTAKE

According to figures on Internet penetration, in 2013 there is still a big gap in terms of users between developing and developed countries (ITU, 2013). These figures show a penetration of 70% approximately for developed countries while only a 30% for the developing ones.

 

Traditionally the digital divide has had a correlation with the difficulties to access (and use[1]) Internet connexion. Those difficulties could be related to access to old computers, high price connexions, among others. Some analysts (Gurstein, 2011) argue that some of these initiatives (open data initiatives, in particular) might present a new divide among the population. Together with the digital divide, the rapid development in ICT tools seems to add new barriers to entry.

 

Current discourses on ICT tools for transparency and accountability suggest (implicitly or sometimes explicitly) that with these new tools everybody can make use of the data and information provided as well as act upon them. However, there are numerous barriers that are not related only to the access to Internet or others technologies (digital divide) but also, as Gurstein mentioned, to the educational resources/skills which would allow for the effective use of those resources.

“…the lack of these foundational requirements means that the exciting new outcomes available from open data are available only to those who are already reasonably well provided for technologically and with other resources.” (Gurstein, 2011)

 

For the community of potential users to be able to interact with the project, they need the necessary skills to use digital technology as well as to manage, and assess information regarding public interest issues. That is, it is important to count with an ICT literate community. This is relevant for government project as well as civil society initiatives.

 “..the release of public sector information without a commensurate increase in data literacy will do little to empower the average citizen.” (Gigler, Custer, & Rahemtulla, 2011)

 

Furthermore, in developing contexts, not only ICT literacy is a key element for the success of a project but also language differences as well as the material factors such as access to low cost technologies (digital divide not only in terms of access to technology but also regarding the skills to effectively make use of those tools). As explained in the Ugandan context:

“A major constraint mentioned […] was funding shortages. This was followed by the high cost of accessing the tools, the capability to use (language and literacy) the mainly Internet or mobile based platforms.” (Kalemera, Nalwoga, & Wakabi, 2012)

 

In that sense, according to Courtney Tolmie, director at the Research for Development Institute, websites that allow reporting in the local languages, and that also receive high levels of publicity, and accept SMS texting (a much more accessible technology in many developing countries), should prove more successful (Dawson, 2012).

 

Even in the absence of some of the above-mentioned barriers, such as an ICT literacy community with an easy access to technology, there is not a guarantee of a robust citizen engagement.

“… increasing the availability of Internet based information does not necessarily mean that citizens will use it to demand greater accountability. The proportion of citizens who are prepared to be consistently engaged in the process of governance is relatively small. Even where there are high rates of Internet penetration, experience has shown that creating a good website or online portal does not guarantee its use” (Bhatnagar, 2003)

 

4.4 CONTEXT

All of the above-mentioned factors can provide insights in terms of user trends and pre-conditions for that uptake. However, when considering technological interventions it is important to consider the legal, policy and social context in which technology is introduced. In that sense, low engagement could also be a result of distrust or poor relationships with the intended users of disclosed information (government). Following Finnegan (2012) “Distrust, animosity and secrecy are commonly cited issues for technology projects working towards government accountability (Finnegan, 2012).

 

A clear example of that limitation to engage with the general public is shown by the experience of the civil society initiative, “Map Kibera”, a community-mapping project. The local mappers working on the project were originally met “with suspicion by residents, and questioned about their right to collect and record information. Some mappers were asked whether they were being paid for their work, or were asked for payment in return for the data they received” (Finnegan, 2012).

 

This poor relationship with government might be also related, among other reasons, to the frustration coming from the absence of institutional mechanisms to submit the input/demand/grievance from the community of users.

 

Even when those mechanisms are in place, the lack of a timely response (or the complete absence of feedback) can lead to apathy from the users. Clear evidence of the use of the data/input collected and their contribution in correcting and/or punishing wrongdoing could incentivize users to engage with anti-corruption ICT projects more in figure. For example, in Bangalore, Bhaskar Rao, the Transport Commissioner for the state of Karnataka, used the data collected on I Paid a Bribe to push through reforms in the motor vehicle department. As a result, and in order to avoid bribes, licenses are now applied for online (Strom, 2012), and citizens have seen an impact from their use of transactional ICTs to report corruption.

 

Anupama Dokeniya explains that “transparency policies will achieve little if the political system does not create the incentives for officials to be sanctioned when corruption is exposed, for service providers to be penalized when poor performance or absenteeism is revealed, or for safeguards or structural reforms to be adopted when evidence of systemic governance problems emerge”  (Dokeniya, 2012). The same logic can be applied to all the ICT-led projects we have surveyed. Technology just provides the tools for a greater number of citizens to access a large amount of information, but the pivotal driver of success in these initiatives are broadly the same as for any other transparency policy.

 

Furthermore, following Finnegan, in many cases, even when there is significant interest from communities of users, if the application or platform is unable to produce any change, the interest and support from those before-enthusiastic users start to fade. Conversely, when participants realize that their contribution could lead to any relevant outcome, the esteem for the tool increases (Finnegan, 2012).

 

4.5 INTERMEDIARIES

To lower those barriers (absence of an ICT literate community, lack of easy access to technology and/or high costs of accessing internet and other technologies), when a project is focused on government’s disclosure of public information (open data initiatives, transparency portals), it is important to count with the presence of intermediaries (centralized users) to amplify and simplify the disclosed data/information. To create awareness among citizens and to provide the tools for those citizens to later scrutinize, assess and hold governments accountable, intermediaries are key actors to engage users with that information, especially in political accountability initiatives as they translate the sometimes abstract ideas and data into simple messages and stories that other citizens can relate to.

 

Genuinely promoting transparency requires the hard work of doing investigative research, publishing reports, and promoting them to the media. Bubble 2.0 hype aside, the fanciest pop-up windows and Google Maps mashups won’t change that.” (Swartz, 2006)

 

Those intermediaries can be social or technical skilled groups. Some of the intermediaries may focus on creating applications to simplify the access and use of the raw data and some others may help with information distribution and citizens’ engagement to demand accountability. As previously mentioned, no every citizen is eager to engage with transparency initiatives (due to a lack of interest, skills or resources), therefore to intermediaries play a key role in the use of those provided ICT tools. The existence and capacity of technically skilled intermediaries is likely to be an important determining factor for the success of many ICT-led interventions, particularly open data interventions.

 

4.6 IMPACT

To present a clear idea about the above-mentioned questions on incentives and desired outcomes could help to the assessment of these interventions. There is no proper impact assessment without the presence of a theory of change.

 

Anecdotal evidence can be found about particular initiatives and some of the changes they produce, however, there is a lack of systematic assessments of these policies and their relationship to greater government transparency, accountability and participation in decision-making. In that sense, there are several recounts of individual initiatives but in terms of developing frameworks to assess each type of ICT initiative, there is a lack of academic research.

 

Moreover, in terms of initiatives related to the disclosure of information (transparency portals and Open Data Initiatives) the idea of counting visits to a website and/or the number of ‘downloads” of certain datasets or documents cannot be presented as indicators of usage, and much less, of impact of any of these policies. In many cases, these initiatives are compared to one another in terms of number of published documents and datasets as well as number of visits. However, these numbers could lead to wrong results, or partial ones at its best.

 

 

References

 

Avila, R., Feigenblatt, H., Heacock, R., & Heller, N. (2011). Global mapping of technology for transparency and accountability: New technologies.

Bhatnagar, S. (2003). E-government and access to information. In Global Corruption Report (pp. 24–32).

Dawson, S. (2012). Citizens wield web tools to combat petty bribery. Thomson Reuters Foundation.

Dimaggio, P., & Hargittai, E. (2001). From the “Digital Divide” to “Digital Inequality”: Studying Internet Use as Penetration Increases.

Dokeniya, A. (2012). #6 from 2012: Opening Government Data. But Why? People, Spaces, Deliberation World Bank Blog. Retrieved from http://blogs.worldbank.org/publicsphere/opening-government-data-why

Finnegan, S. (2012). Using technology for collaborative transparency?: Risks and opportunities. In GIS Watch 2012 (Vol. 8, pp. 29–33).

Fung, A., Gilman, H. R., & Shkabatur, J. (2011). Impact case studies from middle income and developing countries New technologies.

Gigler, B.-S., Custer, S., & Rahemtulla, H. (2011). Realizing the Vision of Open Government Data: Opportunities, Challenges and Pitfalls (Abridged Version).

Gurstein, M. (2011). Open data: Empowering the empowered or effective data use for everyone? First Monday, 16(2).

ITU. (2013). ICT Facts and Figures – The World in 2013.

Kalemera, A., Nalwoga, L., & Wakabi, W. (2012). How ICT tools are promoting citizen participation in Uganda.

Knox, C. (2009). Dealing with sectoral corruption in Bangladesh: Developing citizen involvement. Public Administration and Development, 29(2), 117–132. doi:10.1002/pad.523

Kuriyan, R., Bailur, S., Gigler, B.-S., & Park, K. R. (2012). Technologies for Transparency and Accountability. Washington DC.

Steinberg, T. (2011). Asking the wrong question about Data.gov. Premise (blog). Retrieved from http://steiny.typepad.com/premise/2011/04/asking-the-wrong-question-about-datagov.html

Strom, S. (2012, March 6). I Paid a Bribe and Similar Corruption-Exposing Sites Spread – NYTimes.com. New York Times. New York.

Swartz, A. (2006). Disinfecting the Sunlight Foundation. Aaron Swartz’s Raw Thoughs. Retrieved from http://www.aaronsw.com/weblog/dissunlight



[1] However, it is important that access and use are not necessarily synonymous. Some studies have shown that: “…more people have access than use it (NTIA 1998); and, second, that whereas resources drive access, demand drives intensity of use among people who have access” (Dimaggio & Hargittai, 2001)

 

Thoughts? Reflections? Add a comment on the draft by 23rd November.

ICTs and Anti-Corruption: theory and examples

[Summary: draft section from U4 paper on exploring the incentives for adopting ICT innovation in the fight against corruption]

As mentioned a few days ago, I’ve currently got a paper online for comment which I’m working on with Silvana Fumega for the U4 anti-corruption centre. I’ll be blogging each of the sections here, and if you’ve comments on any element of it, please do drop in comments to the Google Doc draft. 

ICTS AND ANTI-CORRUPTION

Corruption involves the abuse of entrusted power for personal gain (Transparency International, 2009). Grönlund has identified a wide range of actions that can be taken with ICTs to try and combat corruption, from service automation and the creation of online and mobile phone based corruption-reporting channels to the online publication of government transparency information (Grönlund, 2010). In the diagram below we offer eight broad categories of ICTs interventions with a potential role in fighting corruption.

U4-Diagram

These different ICT interventions can be divided between transactional reforms and transparency reforms. Transactional reforms seek to reduce the space for corrupt activity by controlling and automating processes inside government, or seek to increase the detection of corruption by increasing the flow of information into existing government oversight and accountability mechanisms. Often these developments are framed as part of e-government. Transparency reforms, by contrast, focus on increasing external rather than internal control over government actors by making the actions of the state and its agents more visible to citizens, civil society and the private sector. In the diagram, categories of ICT intervention and related examples are positioned along a horizontal axis to indicate, in general, whether these initiatives have emerged as ‘citizen led’ or ‘government led’ projects, and along the vertical axis to indicate whether the focus of these activities is primarily on transactional reforms, or transparency. In practice, where any actual ICT intervention falls is a matter as much of the details of implementation as it is to do with the technology, although we find these archetypes useful to highlight the different emphasis and origins of different ICT-based approaches.

Many ICT innovations for transparency and accountability[1] have emerged from within civil society and the private sector, only later adopted by governments. In this paper our focus is specifically upon government adoption of innovations: when the government is taking the lead role in implementing some technology with an anti-corruption potential, albeit a technology that may have originally been developed elsewhere, and where similar instances of such technologies may still be deployed by groups outside government. For example, civil society groups in a number of jurisdictions have deployed the Alaveteli open source software[2] which brokers the filing of Right to Information act requests online, logging and making public requests to, and replies from, government. Some government agencies have responded by building their own direct portals for filing requests, which co-exist with the civil society run Alaveteli implementations. The question of concern for this paper is why government has chosen to adopt the innovation and provide its own RTI portals.

Although there are different theories of change underlying ICT enabled transactional and transparency reforms, the actual technologies involved can be highly inter-related. For example, digitising information about a public service as part of an e-government management process means that there is data about its performance that can be released through a data portal and subjected to public pressure and scrutiny. Without the back-office systems, no digital records are available to open (Thurston, 2012).

The connection between transactional e-government and anti-corruption has only relatively recently been explored. As Bhatnagar notes, most e-government reforms did not begin as anti-corruption measures. Instead, they were adopted for their promise to modernise government and make it more efficient (Bhatnagar, 2003). Bhatnagar explains that “…reduction of corruption opportunities has often been an incidental benefit, rather than an explicit objective of e-government”. A focus on the connection between e-government and transparency is more recent still. Kim et. al. (2009) note that “E-government’s potential to increase transparency and combat corruption in government administration is gaining popularity in communities of e-government practitioners and researchers…”, arguably as a result of increased Internet diffusion meaning that for the first time data and information from within government can, in theory, be made directly accessible to citizens through computers and mobile phones, without passing through intermediaries.

In any use of ICTs for anti-corruption, the technology itself is only one part of the picture. Legal frameworks, organisational processes, leadership and campaign strategies may all be necessary complements of digital tools in order to secure effective change. ICTs for accountability and anti-corruption have developed in a range of different sectors and in response to many different global trends. In the following paragraphs we survey in more depth the emergence and evolution of three kinds of ICTs with anti-corruption potential, looking at both the technologies and the contexts they are embedded within. 

2.1 TRANSPARENCY PORTALS

A transparency portal is a website where government agencies routinely publish defined sets of information. They are often concerned with financial information and might include details of laws and regulations alongside more dynamic information such as government debt, departmental budget allocations and government spending (Solana, 2004). They tend to have a specific focus, and are often backed by a legal mandate, or regulatory requirement, that information is published to them on an ongoing basis. National transparency portals have existed across Latin America since the early 2000s, developed by finance ministries following over 15 years investment in financial management capacity building in the region. Procurement portals have also become common, linked to efforts to make public procurement more efficient, and comply with regulations and good practice on public tenders.

More recently, a number of governments have mandated the creation of local government transparency portals, or the creation of dedicated transparency pages on local government websites. For example, in the United Kingdom, the Prime Minister requested that governments publish all public spending over £500 on their websites, whilst in the Philippines the Department of Interior and Local Government (DILG) has pushed the implementation of a Full Disclosure Policy requiring Local Government Units to post a summary of revenues collected, funds received, appropriations and disbursement of funds and procurement–related documents on their websites. The Government of the Philippines has also created an online portal to support local government units in publishing the documents demanded by the policy[3].

In focus: Peru Financial Transparency Portal A transparency portal is a website where government agencies routinely publish defined sets of information. They are often concerned with financial information and might include details of laws and regulations alongside more dynamic information such as government debt, departmental budget allocations and government spending.

Country: Peru

Responsible: Government of Peru- Ministry of Economic and Financial Affairs

Brief description: The Peruvian Government implemented a comprehensive transparency strategy in early 2000. That strategy comprised several initiatives (law on access to financial information, promotion of citizen involvement in transparency processes, among others). The Financial Transparency Portal was launched as one of the elements of that strategy. In that regard, Solanas (2003) suggests that the success of the portal is related to the existence of a comprehensive transparency strategy, in which the portal serves as a central element. The Portal (http://www.mef.gob.pe/) started to operate in 2001 and, at that time, it was praised as the most advanced in the region. Several substantial upgrades to the portal have taken place since the launch.

Current situation:

The portal presents several changes from its early days. In the beginning, the portal provided access to documents on economic and financial information. After more than a decade, it currently publishes datasets on several economic and financial topics, which are provided by each of the agencies in charge of producing or collecting the information. Those datasets are divided in 4 main modules: budget performance monitoring, implementation of investment projects, inquiry on transfers to national, local and regional governments, and domestic and external debt. The portal also includes links to request information, under the Peruvian FOI law, as well as track the status of the request.

Sources:

http://www.politikaperu.org/directorio/ficha.asp?id=355

http://www.egov4dev.org/transparency/case/laportals.shtml

http://www.worldbank.org/socialaccountability_sourcebook/Regional%20database/Case%20 studies/Latin%20America%20&%20Caribbean/TOL-V.pdf#page=71

In general, financial transparency portals have focussed on making government records available: often hosting image file version of printed, signed and scanned documents which mean that anyone wanting to analyse the information from across multiple reports must re-type it into spreadsheets or other software. Although a number of aid and budget transparency portals are linked directly to financial management systems, it is only recently that a small number of portals have started to add features giving direct access to datasets on budget and spending.

Some of the most data-centric transparency portals can be found in the International Aid field, where Aid Transparency Portals have been built on top of Aid Management Platforms used by aid-recipient governments to track their donor-funded projects and budgets. Built with funding and support from International donors, aid transparency portals such as those in Timor Leste and Nepal offer search features across a database of projects. In Nepal, donors have funded the geocoding of project information, allowing a visual map of where funding flows are going to be displayed.

Central to the hypothesis underlying the role of transparency portals in anti-corruption is the idea that citizens and civil society will demand and access information from the portals, and will use it to hold authorities to account (Solana, 2004). In many contexts whilst transparency portals have become well-established, direct demand from citizens and civil society for the information they contain remains, as Alves and Heller put it in relation to Brazil’s fiscal transparency, “frustratingly low” (in Khagram, Fung, & Renzio, 2013). However, transparency portals may also be used by the media and other intermediaries, providing an alternative more indirect theory of change in which coverage of episodes of corruption creates electoral pressures (in functioning democracies at least) against corruption. Though, Power and Taylor’s work on democracy and corruption in Brazil suggests that whilst such mechanisms can have impacts, they are often confounded in practice by other non-corruption related factors that influence voters preferences, and a wide range of contingencies, from electoral cycles to political party structures and electoral math (Power & Taylor, 2011).

2.2 OPEN DATA PORTALS

Where transparency portals focus on the publication of specific kinds of information (financial; aid; government projects etc.), open data portals act as a hub for bringing together diverse datasets published by different government departments.

Open data involves the publication of structured machine-readable data files online with explicit permission granted for anyone to re-use the data in any way. This can be contrasted with examples where transparency portals may publish scanned documents that cannot be loaded into data analysis software, or under copyright restrictions that deny citizens or businesses right to re-use the data.  Open data has risen to prominence over the last five years, spurred on by the 2009 Memorandum on Transparency and Open Government from US President Obama (Obama, 2010) which led to the creation of thedata.gov portal, bringing together US government datasets. This built on principles of Open Government Data elaborated in 2007 by a group of activists meeting in Sebastopol California, calling for government to provide data online that was complete, primary (I.e. not edited or interpreted by government before publication), timely, machine-readable, standardised and openly licensed (Malmud & O’Reilly, 2007)

In focus: Kenya Open Data Initiative (KODI) Open data involves the publication of structured machine-readable data files online with explicit permission granted for anyone to re-use the data in any way. Open data portals act as a hub for bringing together diverse datasets published by different government departments. One of those platforms is: Kenya Open Data Initiative (opendata.go.ke)

Country: Kenya

Responsible: Government of Kenya

Brief description:

Around 2008, projects from Ushahidi to M-PESA put Kenya on the map of ICT innovation. Kenyan government – in particular, then-PS Ndemo of the Ministry of Information and Communications – eager to promote and to encourage that market, started to analyze the idea of publishing government datasets for this community of ICT experts to use.  In that quest, he received support from actors outside of the government such as the World Bank, Google and Ushahidi. Adding to that context, in 2010 a new constitution, recognizing the right to access to information by citizens, was enacted in Kenya (however, a FOI law is still a pending task for the Kenyan government). On July 8 2011, President Mwai Kibaki launched the Kenya Open Data Initiative, making government datasets available to the public through a web portal: opendata.go.ke

Current situation:

Several activist and analyst are starting to write about the lack of updates and updated information of the Kenya Open Data Initiative. The portal has not been updated in several months, and its traffic has slowed down significantly.

Sources:

http://www.scribd.com/doc/75642393/Open-Data-Kenya-Long-Version

http://blog.openingparliament.org/post/63629369190/why-kenyas-open-data-portal-is-failing-and-why-it

http://www.code4kenya.org/?p=469

http://www.ict.go.ke/index.php/hot-topic/416-kenya-open-data

http://www.theguardian.com/global-development/poverty-matters/2011/jul/13/kenya-open-data-initiative

Open data portals have caught on as a policy intervention, with hundreds now online across the world, including an increasing number in developing countries. Brazil, India and Kenya all have national open government data portals, and Edo State in Nigeria recently launched one of the first sub-national open data portals on the continent, expressing a hope that it would “become a platform for improving transparency, catalyzing innovation, and enabling social and economic development”[4]. However, a number of open data portals have already turned out to be short-lived, with the Thai governments open data portal launched[5] in 2011, already defunct and offline at the time of writing.

The data hosted on open data portals varies widely: ranging from information on the locations of public services, and government service performance statistics, to public transport timetables, government budgets, and environmental monitoring data gathered by government research institutions. Not all of this data is useful for anti-corruption work: although the availability of information as structured data makes it far easier to third-parties to analyse a wide range of government datasets not traditionally associated with anti-corruption work to look for patterns and issues that might point to causes for concern. In general, theories of change around open data for anti-corruption assume that skilled intermediaries will access, interpret and work with the datasets published, as portals are generally designed with a technical audience in mind.

Data portals can act as both a catalyst of data publication, providing a focal point that encourages departments to publish data that was not otherwise available, and as an entry-point helping actors outside government to locate datasets that are available. At their best they provide a space for engagement between government and citizens, although few currently incorporate strong community features (De Cindio, 2012).

Recently, transparency and open data efforts have also started to focus on the importance of cross-cutting data standards, that can be used to link up data published in different data portals, and to solicit the publication of sectoral data. Again the aid sector has provided a lead here, with the development the International Aid Transparency Initiative (IATI) data standard, and a data portal collating all the information on aid projects published by donors to this standard[6]. New efforts are seeking to build on experiences from IATI with data standards for contracts information in the Open Contracting initiative, which not only targets information from governments, but also potentially disclosure of contract information in the private sector[7].

2.3 CITIZEN REPORTING CHANNELS

Transparency and open data portals primarily focus on the flow of information from government to citizen. Many efforts to challenge corruption require a flow of information the other way: citizens reporting instances of corruption or providing the information agents of government need to identify and address corrupt behaviour. When reports are filed on paper, or to local officials, it can be hard for central governments to ensure reports are adequately addressed. By contrast, with platforms like the E-Grievance Portal in the Indian State of Orissa[8], when reports are submitted they can be tracked, meaning that where there is will to challenge corruption, citizen reports can be better handled.

Many online channels for citizen reporting have in fact grown up outside of government. Platforms like FixMyStreet in the UK, and the many similar platforms across the world, have been launched by civil society groups frustrated at having to deal with government through seemingly antiquated paper processes. FixMyStreet allows citizens to point out on a map where civil infrastructure requires fixing and forward the citizen reports to the relevant level of government. Government agents are invited to report back to the site when the issue is fixed, giving a trackable and transparent record of government responsiveness. In some areas, governments have responded to these platforms by building their own alternative citizen reporting channels, though often without the transparency of the civil society platforms (reports simply go to the public authority; no open tracking is provided), or, in other cases, by working to integrate the civil society provided solution with their own systems.

In focus: I Paid a BribeMany online channels for citizen reporting have been developed outside of government. One of those platforms is “I Paid a Bribe”, and Indian website aimed at collating bribe’s stories and prices from citizens across the country and then use it to present a snapshot of trends in bribery.

Country: India

Responsible: Janaagraha (www.janaagraha.org) a Bangalore based not-for-profit organizatio

Brief description:

The initiative was first launched on August 15, 2010 (India’s Independence Day), and the website became fully functional a month later. I Paid a Bribe aims to understand the role of bribery in public service delivery by transforming the data collected from the reports into knowledge to inform the government about gaps in public transactions and in strengthening citizen engagement to improve the quality of service delivery. For example, in Bangalore, Bhaskar Rao, the Transport Commissioner for the state of Karnataka, used the data collected on I Paid a Bribe to push through reforms in the motor vehicle department. As a result, and in order to avoid bribes, licenses are now applied for online (Strom, 2012).

Current situation: Trying to reach a greater audience, ipaidabribe.com launched, in mid 2013, “Maine Rishwat Di”, the Hindi language version of the website: http://hindi.ipaidabribe.com/ At the same time, they launched Mobile Apps and SMS services in order to make bribe reporting easier and more accessible to citizens all across India. “I paid a Bribe” has also been replicated with partners in a number of other countries such as Pakistan, Kenya,Morocco and Greece, among others.

Sources: https://www.ipaidabribe.com/about-us

http://southasia.oneworld.net/Files/ict_facilitated_access_to_information_innovations.pdf/at_download/file

http://www.firstpost.com/india/after-reporting-bribes-now-report-rishwats-hindi-version-of-i-paid-a-bribe-launched-1022627.html

http://www.ipaidabribe.com/comment-pieces/“maine-rishwat-di”-hindi-language-version-ipaidabribecom-launched-shankar-mahadevan

Strom, Stephanie (2012) Web Sites Shine Light on Petty Bribery Worldwide. The New York Times. March 6th. Available:  http://www.nytimes.com/2012/03/07/business/web-sites-shine-light-on-petty-bribery-worldwide.html

References

Bhatnagar, S. (2003). Transparency and Corruption?: Does E-Government Help??, 1–9.

De Cindio, F. (2012, April 4). Guidelines for Designing Deliberative Digital Habitats: Learning from e-Participation for Open Data Initiatives. The Journal of Community Informatics.

Fox, J. (2007). The uncertain relationship between transparency and accountability. Development in Practice, 17(4-5), 663–671. doi:10.1080/09614520701469955

Grönlund, Å. (2010). Using ICT to combat corruption – tools, methods and results. In C. Strand (Ed.), Increasing transparency and fighting corruption through ICT: empowering people and communities (pp. 7–26). SPIDER.

Khagram, S., Fung, A., & Renzio, P. de. (2013). Open Budgets: The Political Economy of Transparency, Participation, and Accountability (p. 264). Brookings Institution Press.

Kim, S., Kim, H. J., & Lee, H. (2009). An institutional analysis of an e-government system for anti-corruption: The case of OPEN. Government Information Quarterly, 26(1), 42–50. doi:10.1016/j.giq.2008.09.002

Malmud, C., & O’Reilly, T. (2007, December). 8 Principles of Open Government Data. Retrieved June 01, 2010, from http://resource.org/8_principles.html

Obama, B. (2010). Memo from President Obama on Transparency and Open Government (in Open Government: Collaboration, Transparency and Participation in Practice. In D. Lathrop & L. Ruma (Eds.), .

Power, T. J., & Taylor, M. M. (2011). Corruption and Democracy in Brazil: The struggle for accountability. University of Notre Dame.

Solana, M. (2004). Transparency Portals: Delivering public financial information to Citizens in Latin America. In K. Bain, I. Franka Braun, N. John-Abraham, & M. Peñuela (Eds.), Thinking Out Loud V: Innovative Case Studies on Participatory Instruments (pp. 71–80). World Bank.

Thurston, A. C. (2012). Trustworthy Records and Open Data. The Journal of Community Informatics, 8(2).

Transparency International. (2009). The Anti-Corruption Plain Language Guide.


[1] It is important to clarify that transparency does not necessarily lead to accountability. Transparency, understood as the disclosure of information that sheds light on institutional behavior, can be also defined as answerability. However, accountability (or “hard accountability” according to Fox, 2007) not only implies answerability but also the possibility of sanctions (Fox, 2007).

[2] http://www.alaveteli.org/about/where-has-alaveteli-been-installed/

[4] http://data.edostate.gov.ng/ Accessed 10th October 2013

[8] http://cmgcorissa.gov.in

Can the G8 Open Data Charter deliver real transparency?

[Summary: cross-post of an article reflecting on the G8 Open Data Charter]

I was asked by The Conversation, a new journalism platform based around linking academic writers with professional journalists and editors, to put together a short article on the recent G8 Open Data Charter, looking at the potential for it to deliver on transparency. The result is now live over on The Conversation site, and pasted in below (under a Creative Commons license). 

Last week G8 leaders signed up to an Open Data Charter, calling for government datasets to be “open data by default”. Open data has risen up the government agenda in the UK over the last three years, with the UK positioning itself as a world leader. But what does the charter mean for G8 nations, and more broadly, will it deliver on the promise of economic impacts and improved governance through the open release of government data relating to matters such as crime figures, energy consumption and election results?

Open government data (OGD) has rapidly developed from being the niche interest of a small community of geeks to a high-profile policy idea. The basic premise of OGD is that when governments publish datasets online, in digital formats that can be easily imported into other software tools, and under legal terms that permit anyone to re-use them (including commercially), those outside government can use that data to develop new ideas, apps and businesses. It also allows citizens to better scrutinise government and hold authorities to account. But for that to happen, the kind of data released, and its quality, matter.

As the Open Knowledge Foundation outlined ahead of the G8 Summit in a release from its Open Data Census “G8 countries still have a long way to go in releasing essential information as open data”. Less than 50% of the core datasets the census lists for G8 members are fully available as open data. And because open data is one of the most common commitments made by governments when they join the wider Open Government Partnership (OGP), campaigners want a clear set of standards for what makes a good open data initiative. The G8 Open Data Charter provides an opportunity to elaborate this. In a clear nod towards the OGP, the G8 charter states: “In the spirit of openness we offer this Open Data Charter for consideration by other countries, multinational organisations and initiatives.”

But can the charter really deliver? Russia, the worst scoring G8 member on the Open Data Census, and next chair of the G8, recently withdrew from the OGP, yet signed up to the Charter. Even the UK’s commitment to “open data by default” is undermined by David Cameron’s admission that the register of company beneficial ownership announced as part of G8 pledges on tax transparency will only be accessible to government officials, rather than being the open dataset campaigners had asked for.

The ability of Russia to sign up to the Open Data Charter is down to what Robison and Yu have called the “Ambiguity of Open Government” — the dual role of open data as a tool for transparency and accountability and for economic growth. As Christian Langehenke explains, Russia is interested in the latter, but was uncomfortable with the focus placed on the former in the OGP. The G8 Charter covers both benefits of open data but is relatively vague when it comes to the release of data for improved governance.

However, if delivered, the specific commitments made in the technical annexe to opening national election and budget datasets, and to improving their quality by December 2013, would signal progress for a number of states, Russia included. Elsewhere in the G8 communiqué, states also committed to publishing open data on aid to the International Aid Transparency Initiative standard, representing new commitments from France, Italy and Japan.

The impacts of the charter may also be felt in Germany and in Canada, where open data campaigners have long been pushing for greater progress to release datasets.Canadian campaigner David Eaves highlights in particular how the charter commitment to open specific “high value” datasets goes beyond anything in existing Canadian policy. Although the pressure of next year’s G8 progress report might not provide a significant stick to spur on action, the charter does give campaigners in Canada, Germany other other G8 nations a new lever in pushing for greater publication of data from their governments.

Delivering improved governance and economic growth will not come from the release of data alone. The charter offers some recognition of this, committing states to “work to increase open data literacy” and “encourage innovative uses of our data through the organisation of challenges, prizes or mentoring”. However, it stops short of considering other mechanisms needed to unlock the democratic and governance reform potential of open data. At best it frames data on public services as enabling citizens to “make better informed choices about the services they receive”, encapsulating a notion of citizen as consumer (a framing Jo Bates refers to the as the co-option of open data agendas), rather than committing to build mechanisms for citizens to engage with the policy process, and thus achieve accountability, on the basis of the data that is made available.

The charter marks the continued rise of open data to becoming a key component of modern governance. Yet, the publication of open data alone stops short of the wider institutional reforms needed to deliver modernised and accountable governance. Whether the charter can secure solid open data foundations on which these wider reforms can be built is something only time will tell.