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Context: The Gopalakrishnan Committee set up by the government on developing a governance framework for non-personal data recently put out its draft report for public consultation. 


  • Data is almost the most valuable economic resource today. Whoever collects data de facto owns its economic value. Seven out of the top 10 companies globally by market capitalization are data-centric.
  • The present situation of data’s non-governance in economic terms suits the powerful actors that dominate digitally across the globe – US and Chinese companies and their respective governments. 
  • Some laws and rights do exist around an individual’s personal data, but they are mostly about protection from harm (privacy, for instance). There are no real economic rights to data.
  • There are calls worldwide to break up Big Tech; to moderate their monopoly power. 
  • It is in this context that a committee set up by the government on governing non-personal data, headed by Kris Gopalakrishnan, co-founder of Infosys recently put its draft report for public consultation. 
  • The report’s main purpose is to ensure wide sharing and availability of data in society

Need for a strong and fair digital economy:

  • The infrastructural nature of data: Industrial age infrastructure — roads, electricity, etc. — were often publicly owned. The idea was to ensure the widespread availability of such infrastructural elements to all and avoid wasteful duplications. Society’s data have a similar nature to a digital economy.
  • Non-personal data, which includes anonymised data is increasingly becoming almost as important as personal data. It is the real fuel for artificial intelligence (AI). 
  • Digital vertical integration: Through over-the-top services, very few corporations have vertically integrated all the digital components involved in delivery of any digital service. 
  • Digital monopoly: 
    • Such an unsustainable concentration of digital power has a significant geopolitical dimension, with complete domination globally of U.S. and Chinese companies. 
    • At the national level it results in exploitation of consumers and small economic actors, and of strangulating competition and innovation. 
    • Their monopoly is best addressed by separating the infrastructural elements of digital service provision from the business of digital service delivery. 

Recommendation of the Gopalakrishnan Committee: 

  • Treat data as infrastructure, or ‘commons’, so that data is widely available for all businesses. 
  • It has classified non-personal data into three main categories, namely 
    • Public non-personal data, 
    • Community non-personal data and 
    • Private non-personal data.
  • The non-personal data generated in the country should be allowed to be harnessed by various domestic companies and entities. Data from privately owned sources remain private. 
  • Community data: Only the data collected from non-privately owned sources, from society or community sources, have to be shared when requested for. 
    • The committee introduces the concept of legal community trustees that could be various bodies representative of the community.
  • Sensitive non personal data: The non-personal data arising from sensitive personal data like national security or a community health data may be considered as sensitive non-personal data.
    • Even if the data is about the health of a community or a group of communities, though it may be in anonymised form, it can still be dangerous.
  • The committee recommends a new legislation, because ensuring and enforcing data sharing will require sufficient legal backing. 
  • Set up a new authority which would be empowered to monitor the use and mining of non-personal data.

What is non-personal data?

  • In its most basic form, non-personal data is any set of data which does not contain personally identifiable information. This in essence means that no individual or living person can be identified by looking at such data.
  • Unlike personal data, which contains explicit information about a person’s name, age, gender, sexual orientation, biometrics and other genetic details, non-personal data is more likely to be in an anonymised form.
  • For example, while order details collected by a food delivery service will have the name, age, gender, and other contact information of an individual, it will become non-personal data if the identifiers such as name and contact information are taken out.

What are public, community, and private non-personal data sets?

  • All the data collected by government and its agencies such as census, data collected by municipal corporations on the total tax receipts in a particular period or any information collected during execution of all publicly funded works has been kept under the umbrella of public non-personal data.
  • Any data identifiers about a set of people who have either the same geographic location, religion, job, or other common social interests will form the community non-personal data. 
    • For example, the metadata collected by ride-hailing apps, telecom companies, electricity distribution companies among others have been put under the community non-personal data category by the committee.
  • Private non-personal data can be defined as those which are produced by individuals which can be derived from application of proprietary software or knowledge.


Significance of the report: There are two key infrastructural components of a digital economy: data and cloud computing. 

  • Focuses on the infrastructural element of data: Infrastructures are to be equitably provided for all businesses. Data has similar characteristics.

  • Reducing digital dependence
    • Community ownership’ means that the data should be shared back with all those who need it in society, whether to develop domestic digital businesses or for producing important digital public goods. 
    • With a robust domestic data/AI industry, dependence on U.S. and Chinese companies will reduce.
  • Data should be open to citizens
    • This will improve accountability. This is one of the reasons why the Right to Information (RTI) Act, 2005, mandates the disclosure of government data on a suo moto basis. 
    • If taxpayer money has funded any of the data sets, then it is an obligation of the state to return the fruits of that funding to the taxpayer. 
    • By permitting the reuse of government data sets, we avoid the need for duplication.
    • Government data sets, curated according to publicly verified standards, can lead to increased confidence in data quality and increased usage.
    • One of the nine pillars of the Digital India Policy is “information for all”. 
    • The National Data Sharing and Accessibility Policy (NDSAP), 2012 requires all non-sensitive information held by public authorities to be made publicly accessible in machine readable formats (subject to conditions). 
    • The government has also set up an Open Government Data Platform to provide open access to data sets held by ministries and other agencies of the government. 

Issues with the recommendations:

  • Ignores state interference in the private data ecosystem
    • The Gopalakrishnan Committee could have evaluated what is going wrong with existing policies and practice pertaining to government data. Instead, the report largely focuses on the dangers posed by data collection by private sector entities.
    • Some of the most important non-personal data sets are held by the government, or result from taxpayer funding. 
    • India’s cybersecurity framework continues to be woefully inadequate, while even the Justice B.N. Srikrishna Committee report of 2018 highlighted the need to restrict the growing power of the state to carry out surveillance.
  • Failure to create an open data society

    • There are two reasons for our failure to create an open data-based society. 
      • The first is lack of clarity in some of the provisions of the NDSAP or the relevant implementation guidelines. 
      • The second is the inability to enforce guidelines appropriately, which has meant that data sets released by governments are often inconsistent, incomplete, outdated, published in non-machine readable or inconsistent formats. 
  • Vague community rights: Non-personal data often constitutes protected trade secrets and often raises significant privacy concerns. The paper proposes the nebulous concept of community data while failing to adequately provide for community rights.

Since data governance is a relatively new concept in India, the government should begin with reforming how the government itself deals with citizens’ data. This would endanger greater trust in data governance practices and, importantly, allow the development of state capacity to govern the data ecosystem. 

The global standards on non-personal data

  • In May 2019, the European Union came out with a regulation framework for the free flow of non-personal data in the European Union, in which it suggested that member states of the union would cooperate with each other when it came to data sharing.


After reading this article, answer the following question for Mains answer writing practice. Also you can get your answer checked free of cost by clicking on the following link.

For Mains:

Q) There is a strong need for a strong and fair digital economy. Discuss in light of the report submitted by the Gopalakrishnan Committee set up by the government on developing a governance framework for non-personal data. (15M, 250 Words)