Context

The Draft India Data Accessibility and Use Policy 2022 released in February for public consultation, is silent on the norms, rules, and mechanisms to bring to fruition its vision.

Aims of the policy

• The Draft Policy aims for harnessing public sector data for informed decision-making, citizen-centric delivery of public services, and economy-wide digital innovation.
• It seeks to maximise access to and use of quality non-personal data (NPD) available with the public sector, overcoming a number of historical bottlenecks.
• This GovTech 3.0 approach — to unlock the valuable resource of public sector data — does upgrade the OGD vision of the National Data Sharing and Accessibility Policy (NDSAP), 2012.
• It seeks to harness data-based intelligence for governance and economic development.

What is lacking in the draft policy?

• Lacking in norms and rules: The Draft Policy is silent on the norms, rules, and mechanisms to bring to fruition its vision of data-supported social transformation.
• Ignores the canons of RTI: Any attempt to promote meaningful citizen engagement with data cannot afford to ignore the canons of the Right to Information (RTI), and hence, the need for certain citizen data sets with personal identifiers to be in the public domain, towards making proactive disclosure meaningful.
•  The unfinished task of the NDSAP in bringing coherence between restrictions on the availability of sensitive personal information in the public domain and India’s RTI, therefore, has been lost sight of.
• Risks to group privacy: With respect to government-to-government data sharing for citizen-centric service delivery, the Draft Policy highlights that approved data inventories will be federated into a government-wide, searchable database.
•  But even in the case of anonymised citizen data sets (that is no longer personal data), downstream processing can pose serious risks to group privacy.
• Lack of data trusteeship framework: The Draft Policy adheres to the NDSAP paradigm of treating government agencies as ‘owners’ of the data sets they have collected and compiled instead of shifting to the trusteeship paradigm recommended by the 2020 Report of the MEITY Committee of Experts on non-personal data governance.
• The lack of a data trusteeship framework gives government agencies unilateral privileges to determine the terms of data licensing.

Suggestions

• Taking on board a trusteeship-based approach, the proposed Draft Policy must pay attention to data quality, and ensure that licensing frameworks and any associated costs do not pose an impediment to data accessibility for non-commercial purposes.
• Create common and interoperable data spaces: In the current context, where the most valuable data resources are held by the private sector, it is increasingly evident to policymakers that socioeconomic innovation depends on the state’s ability to catalyse wide-ranging data-sharing from both public and private sector actors across various sectors.
• The European Union, for instance, has focused on the creation of common, interoperable data spaces to encourage voluntary data-sharing in specific domains such as health, energy and agriculture.
• Mandatory data sharing arrangement: Creating the right conditions for voluntary data-sharing is a necessary, but not sufficient, condition for democratising data innovation.
• In this regard, the data stewardship model for high-value data sets proposed by the MEITY’s Committee of Experts in their Report on Non-Personal Data Governance (2020) is instructive.
• In this model, a government/not-for-profit organisation may request the Non-Personal Data Authority or NPDA for the creation of a high-value data set (only non-personal data) in a particular sector, demonstrating the specific public interest purpose.
• Once such a request is approved by the NPDA, the data trustee has the right to request data-sharing from all major custodians of data sets corresponding to the high-value data set category in question – both public and private.

Conclusion

• What we need is a new social contract for data whereby:
• a) the social commons of data are governed as an inappropriable commons that belong to all citizens;
• b) the government is the custodian or trustee with fiduciary responsibility to promote data use for public good; and
• c) democratisation of data value is ensured through accountable institutional mechanisms for data governance.

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