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National Data Governance Framework Policy

  • Context (TH): The Ministry of Electronics and Information Technology (MeiTY) released the National Data Governance Framework Policy (NPD Framework).
  • As per a NASSCOM report, data and artificial intelligence (AI) can add approximately $450-500 billion to India’s GDP by 2025.

NPD Framework

  • Kris Gopalakrishnan committee: The committee discussed the risks of de-anonymising NPD, the institutionalisation of a central authority for NPD, and ownership and data sharing mechanisms.
  • The Ministry of Electronics and Information Technology (MeiTY) released the National Data Governance Framework Policy (NPD Framework) based on this.
  • Data businesses: This is a new category of business in the country. Entities (including government agencies) that collect, process, or store data beyond a threshold will be classified as data businesses.
  • Sharing of non-personal data: Data-sharing requests for sovereign, public interest, or economic purposes may be made with or without remuneration, depending on processing cost.
  • Open metadata: Sharing metadata, including government metadata, to encourage innovation.

Analysis of the NPD Framework

  • Abstract high-level principles and objectives: Lacks tangible, actionable guidance to achieve.
  • Rights and obligations: Silent on stakeholder rights and obligations across sectors.
  • Pricing and legal mechanisms: Such structures and solutions for data exchange are not addressed.
  • The absence of standardised governance tools aggravates challenges.

Need for NPD Regulation Revamp

  • Unprotected inter-flow of NPD across various stakeholders makes it vulnerable to privacy breaches.
  • The imperfect analysis of crucial public trends can result in faulty decision-making.
  • Inefficient data fails to unlock the power of interdisciplinary legislative and policy-making.
  • By creating a regulatory design for data exchanges in India, public welfare functions can be digitised and automated to a large extent.
  • This will reduce administrative burden and facilitate inter-sectoral integration, making the digitisation of civic functions more participatory.
  • Still, no policy provides for an enforceable regime for NPD in India.

Examples of Data Utilisation for Governance

  • Telangana has designed an agriculture data exchange.
  • Ministry of Housing & Urban Affairs has established the India Urban Data Exchange in collaboration with the Indian Institute of Science.
  • Department of Science & Technology has announced its intention to set up data exchanges to implement aspects of the National Geospatial Policy.

Types of data

  • Personal Data: Contains identifiers through which an individual can be mapped.
  • Non-Personal Data (NPD): Data which excludes personal data.
  • NPD constitutes the primary kind of citizen data obtained by the government, which has the potential to serve as a ‘public good’.

Classification of Non-Personal data (NPD)

  1. Public NPD: Data collected or generated by the government in the course of publicly funded works. For example, anonymised data from land records or vehicle registration can be considered public non-personal data.
  2. Community NPD: Raw or factual data (without any processing) sourced from a community of natural persons (ex., municipal corporations or public electric utilities).
  3. Private NPD: Data collected or generated by private entities through privately owned processes (derived insights, algorithms, or proprietary knowledge).
  • Data principal: The entity to whom the non-personal data relates. This entity can be an individual, a community, or a company.
  • Data custodian: Collects, stores, and processes data in the best interest of the data principal.
  • Data trustee: Representative entity through which Data principals may exercise their rights.
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