Unlike the subsequent two plays, this play focuses on the role of a specific stakeholder – the public sector. This focus on the public sector is a result of the critical role the public sector has in ensuring the growth and sustainability of data stewardship initiatives. To start with, data stewardship needs a robust policy ecosystem to aid its functioning. Recognised rights over data, established means of grievance redressal, and protocols for collection and sharing of data are all key tools that data stewards leverage in their work. These tools are best put in place through policy action by the public sector. The Subject Access and Data Portability rights in the EU GDPR and UK’s Data Rights Act, 2018 (which mirrors rights from the EU GDPR) provide individuals with the right to access data about them held by a company and have an explanation as to why they collect this data, who and who they share it with. These rights have had far reaching ramifications for Uber drivers in the UK and Netherlands who were able to access their data held by Uber to prove that they were entitled to benefits as regular employees / workers and were not self-employed contractors.

Policy action can also serve to inhibit the working of stewards. For example, the EU Data Governance Act’s characterisation of rights under the GDPR in the context of data cooperatives (recital 31) has led to debate around the ability of data cooperatives to function to their full potential. It notes that these rights are personal rights of the data subject that cannot be waived. A possible interpretation of this is that data principal’s cannot delegate their rights to a data cooperative. This evident ban on data mandatability has had serious repercussions for the functioning of data stewards – as they will now be unable to access data rights on behalf of their members. In order to function, stewards will need to either collect data from members directly through an application – something that is expensive to do – or have members individually request data from companies – something that dissuades members from joining a steward. It must be noted that this interpretation would be in sharp contrast to the broader data protection goals of the EU. Nonetheless, what is clear is that the public sector – through its role as a policymaker – has immense sway in the sustenance of data stewards.

Policy making is not the only sphere of influence for the public sector. Active support (financial and otherwise) from the public sector can be a major boon to data stewardship efforts that either don’t yet have a self-sustaining business model or where access to private funding is not easily available. While the other plays also addressed aspects of the public sector’s role, this play looks at the challenges faced with the engagement of the public sector with stewardship and community-oriented initiatives and suggest possible pathways for redress.

Diagnosis of challenges – What are the challenges around public sector engagement with the stewardship ecosystem?

Quicklinks

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Our research – including desk research and conversations with data stewards and other community-oriented organisations – highlighted that funding for community-oriented efforts from the public sector was a point of serious concern, and this was echoed in the conversations we had with organisations in this space. Issues highlighted by organisations include limited access to funding from public sector sources as well as the majority of funding going towards efforts that were directed at the more institutional collection of data that does not involve citizens in the collection and contribution process. These efforts tend to miss out on data points that realistically cannot be obtained through other means.

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Public sector organisations can look to set up national or regional level funding programs aimed at funding data stewardship efforts specifically. In doing so, the programs can have separate funding packages for different focus areas – thus helping to address multiple areas that suffer from a lack of data collection, as was the case with the UK government’s data trusts program, that funded stewardship initiatives aiming to tackle illegal wildlife trade and reduce food waste. These funding programs can be set up by national or state governments as well as public sector organisations, or multilateral bodies. For example, the Global Partnership on AI – a multilateral organisation comprising various national governments – has funded research projects to look at the viability of data trusts to tackle climate change related issues. While the division of funds set out by national or state governments can be for broader thematic areas / practices, funds from public sector organisations can be divided to specific sub-groups within their practice domain, thus helping address data gaps at a minute level. In order to ensure that such funding efforts are stable, it is also important that they are a sustained policy effort and not one-off projects. The European Commission, with its Horizon 2020, launched a program that, inter alia, funded community centric research and innovation efforts. This was succeeded by Horizon Europe, a program with a similar objective. These programs have funded initiatives like the Community Observation Measurement & Participation in AIR Science (COMPAIR) that focuses on increasing citizens’ capacity to monitor, understand and change their environmental impact in relation to air quality. The availability of long-term funding for these efforts can go a long way in ensuring their sustainability. Community Observation Measurement & Participation in AIR Science (COMPAIR) that focuses on increasing citizens’ capacity to monitor, understand and change their environmental impact in relation to air quality. The availability of long term funding for these efforts can go a long way in ensuring their sustainability.

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While the public sector is a key source of funding for data stewardship efforts, it is not the only one. As outlined in other plays, the private sector also has a major role to play in funding and sustaining community-oriented models. While certain philanthropic funds provide funding for data stewardship efforts, the public sector can also enact policy measures to increase the funding of private entities in data stewardship efforts. A key way this can be done is to include data stewardship efforts as a specific activity within Corporate Social Responsibility (CSR) legislations, thereby providing an incentive for corporates to fund such efforts. Further, public sector institutions can also provide certification or validation to data stewards that have a proven track record, assuring corporations of the quality of work of such organisations.

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Citizen generated data has enormous potential to become valuable sources for policymaking. To fully utilise its value, governments need to assess whether the data generated is fit-for-purpose to make informed decisions. To this end, governments need to consider the quality, interoperability and formats of the data and collaborate in a way that such citizen generated data contributes to policy making. The onus is on the policy makers to meaningfully engage such that these efforts are aligned to policy objectives – this can happen through deep collaboration and by building trust with the community. Engaging with a community provides a public sector actor with a more grounded and realistic understanding of the issues facing the community, thereby allowing them to get a better grasp of the sort of data that needs to be collected. Partnering with local organisations / partners in the community can also address issues of capacity that a public sector actor might face, and in many cases provide a more accurate landscape of the issues – citizens might not feel entirely comfortable in providing public sector actors with the truth, or in some cases might exaggerate the situation in the hopes of seeing expedited action.

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Stakeholder engagement / public consultations are a major component in designing policy that is reflective of the needs, concerns and capacities of the relevant subject area. However, in many cases, these consultation processes are not truly bottomup, and lead to the exclusion of key stakeholders. For example, when the Indian Ministry of Agriculture and Farmers’ Welfare sought to implement a digitisation initiative in the sector in India, they released a foundational document outlining their vision and invited comments from the public on this. However, not only was this document released without any consultation with farmers – the one stakeholder most likely to be affected by the policy – this document was released only in English, in a country where most farmers are not literate in English. This put the onus on the civil society to either translate documents into languages that farmers could access, or to explain the policy measures outlined in the document. Policy design processes can be exclusionary in numerous other ways – but a focus on identifying the key communities and stakeholders likely to be affected by policy measures, and then engaging actively with these communities at various stages of the policy making process right from inception, can address this issue. Hearing, firsthand, the needs and challenges of the community in building data stewarding efforts can go a long way in making the consultation process more inclusive and result in a much more effective policy.

Finally, efforts such as the EUROCITIES Citizen Data Principles are also very effective in displaying the commitment of public sector actors to engaging with citizens and instituting inclusive engagement and consultation practices. This has been taken a step further with the DECODE Project in the cities of Amsterdam and Barcelona, where actual tools were created to allow citizens to allow their personal data to be used for public good, on their own terms.

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Collecting data that is then not put to use, or does not result in change in policy, can often have a demoralising effect on citizens – disillusioning them and reducing participation in future efforts. Policies that are tuned to address the needs and challenges expressed by communities – and represented in the data and information they collect – can go a long way in encouraging further participation from communities. A great way to demonstrate that the policy has been informed by community actions, is to provide explanatory notes to policies that provide the rationale for a particular policy measure and include data and information shared by the community as supporting evidence for the nature of policy action being proposed. By showing the community that the public sector is willing to believe in the data collected by the community, and act on it, responsive policies also help increase trust in public sector actors. For example, the European Union released a research report that explored various citizen science efforts with the aim of providing the European Commission with an evidence base of citizen science activities that can support environmental policies in the European Union. The report ended with recommendations on how to leverage the contribution of citizen science to environmental policy. Such policy directives, taken in tandem with funding efforts such as Horizon Europe (mentioned above) can only serve to spur new data stewarding efforts.

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A major issue with community generated data often highlighted by public sector actors is the quality and authenticity of data. This is a fair concern, as citizen generated data is often through low-cost and accessible digital technologies that may not necessarily be of the required standard for policy implementation. Policymakers need to make sure that validation and quality assurance methods are employed by data stewarding initiatives. To ensure a minimum standard of data quality, a plan or protocol can be set out by policymaking bodies or sectoral regulators that lay down standard operating procedures and quality assurance methodology that can be followed. In doing so, the relevant actors can also provide  toolkits that translate technical standards and processes into language that is easier to understand for everyday citizens, thus improving accessibility. The United States’ Environmental Protection Agency provides a great example in this regard with their Citizen Science Central Toolkit and quality assurance methodology.

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Easier availability of public sector data opens doors for countless opportunities to enhance targeted and informed research efforts by data stewards. This is steadily being recognized by policymakers world over as they look to make more public sector data available to encourage research and innovation. However, data held by the public sector is often retained in closed silos for numerous reasons. In cases where data is made available, the problem of access is exacerbated by the modalities of access which are often exclusionary or involve bureaucratic processes – disincentivizing community members from attempting to access such data.

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Policymakers need to create an ecosystem to enhance greater collaboration between government and stakeholders. Policymakers must release information at required quality levels to improve the widespread reporting efforts. The use of open digital infrastructure and tools can promote access to environment data and facilitate collaboration with various stakeholders. Using shared standards and APIs can boost the integration of citizen generated data with official datasets. Using open-source software in citizen generated data would also allow full control of procedures and workflows, which enhances reliability and encourages open transparent and fully documented practice.

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An oft-highlighted problem with the digital economy as it stands today is the fact that significant data collection efforts are being carried out by private companies that wall off these datasets in private silos. The data that companies collect can have immense value to the public – for example, mobility data collected by companies like Uber, Ola, and Lyft can provide governments and city planners with valuable insight to design better public infrastructure and tweak policy for improved sustainability. While Uber has taken a small step towards this by sharing some of the data it collects through the Uber Movement platform, this initiative is nowhere near enough. It does not provide information on where people start and end most of their trips, which is key to understanding commute patterns. Additionally, the Movement platform shares data only for a select handful of cities, despite Uber’s large global presence. Such siloing of data in private hands is playing out across various sectors including agriculture, pharmaceuticals, and energy. This trend of siloed data is no surprise however, given the distinct lack of incentive on private entities to share this data.

Complicating the issue of private sector involvement in data governance for public good is their compliance with regulations designed to provide citizens with greater control over their data. For example, even though the EU GDPR recognises rights of access, correction and deletion, the modalities of this can be very difficult, designed in a way to dissuade from effectively exercising these rights. A report by Worker Info Exchange highlights the problematic behaviour of companies in responding to data access requests, with companies often providing data in nonmachine-readable formats or not even providing certain data that was requested. Additionally, while such rights are critical to empowering individuals over their data, they presuppose a degree of literacy, interest and ability to assert data rights, which are often missing, especially in Global South contexts. While data stewards can play a key role in enabling citizens to assert their rights, they need to be empowered to do so.

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The public sector can play a crucial role in improving the availability of privately held data by incentivising the private sector to share data with the public sector. The simplest method that we see this taking place in is through regulation that mandates the private sector to share data. For example, in India, the ‘Karnataka On-demand Transportation Technology Aggregators’ Rules require cab aggregators to provide records of passenger details, trip origin and destination, and fare collected on demand from authorities. Similarly, the Convention on Biodiversity, an international treaty, has set up a system that allows for fair and equitable sharing of genetic resources. This, along with the Bermuda Principles, have been key in the rapid development of a COVID vaccine through the open sharing of data. The Committee of Experts on Non-Personal Data Governance Framework in India, in their report, highlighted the need for a mandatory regime of NPD sharing in public interest. While such a mandatory regime might be problematic and does not adequately account for business interests and intellectual property, our research has shown that an ecosystem-based voluntary approach to data sharing which focuses on enabling infrastructure, incentivising sharing, and adopts a voluntary structure at its core can be extremely beneficial in getting the private sector to share data for public good.

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While incentivizing data sharing through regulation and improved infrastructure are crucial steps to improving availability of privately held data, they are not always enough. In the case of the Karnataka cab aggregator rules mentioned in the previous strategy, a lack of enforcement has meant that there is no easy public access to the data collected by cab aggregators. Similarly, as highlighted above, individuals are facing it hard to assert their rights under the GDPR, with companies engaging in bad faith practices that disincentivise individuals from further engaging with their rights. This stems from a combination of a lack of well-defined regulations as well as a lack of capacity from regulators. development of a COVID vaccine through the open sharing of data. The Committee of Experts on Non-Personal Data Governance Framework in India, in their report, highlighted the need for a mandatory regime of NPD sharing in public interest. While such a mandatory regime might be problematic and does not adequately account for business interests and intellectual property, our research has shown that an ecosystem-based voluntary approach to data sharing which focuses on enabling infrastructure, incentivising sharing, and adopts a voluntary structure at its core can be extremely beneficial in getting the private sector to share data for public good.

Rather than overburdening regulators, governments can instead empower verified, trusted, independent data stewards to perform the role of an intermediary that ensures accountability. Regulations that provide data stewards with the ability to request information from private companies, under strict guidelines, can go a long way in ensuring accountability in data sharing. For example, Worker Info Exchange facilitates data requests on behalf of gig workers from companies such as Uber, Ola and Deliveroo. In doing so, they take away the burden of data requests from individual drivers and are also in a better position to ensure compliance with such requests from companies. Optery is another example that facilitates data deletion requests for consumers.

Regulation can also be designed in a manner to support stewards to do this. While the GDPR is largely silent on the ability of an individual to delegate their rights, and the Data Governance Act is contentiously worded on data principals’ ability to delegate their rights from the GDPR, academics have assessed legal bases for how delegation of data rights can be carried out under the GDPR. Legislative clarity on this will empower data stewards to better assert and enforce rights of individuals with their consent, in their interest.