This event report is based on a webcast discussion on “Comprehensive Data Governance: Evolution, Challenges, and the Way Forward for Policy” by Prof. Susan Ariel Aaronson. The event is organized by the Generation Alpha Data Center (GenAlphaDC) at IMPRI Impact and Policy Research Institute, New Delhi.
The distinguished speaker was Prof Susan Ariel Aaronson, Research Professor of International Affairs, and Director, Digital Trade and Data Governance Hub, Elliott School of International Affairs, The George Washington University, Washington, DC, USA. Discussant was Ms. Urvashi Prasad, Director, Development Monitoring and Evaluation Office (DMEO), NITI Aayog
Introduction and Opening Remarks
The Web Policy Talk session on the topic of Comprehensive Data Governance was initiated by Mahima Kapoor where she went on to introduce Dr Susan Ariel Aaronson and opened the floor for her detailed presentation. The lecture is based on The State of Statistics – #DataDisclosure series where the Current State, Challenges, and the Way Forward were discussed from a policy point of view in the domain of Data Governance.
The Difficulties of Data Governance
Data is the most collected, analyzed, shared, and traded ‘good’ and/or ‘service’ around the world. Therefore, policymakers know how to govern statistical data and proprietary data (such as trade secrets). The collected data has to be governed in a more transparent, equitable, and accountable manner. With the new influx of big data, governance is becoming increasingly difficult with regard to data governance. The Organisation for Economic Co-operation and Development (OECD)defines Data Governance as principles, policies, standards, laws, regulations, and agreements designed to control, manage, share, protect and extract value from various types of data.
Dimensions of a comprehensive approach to Data Governance
In order to have a comprehensive approach to data governance, it is important to be strategic and create plans for the different contexts of data use and reuse. We must also account for the regulatory measures and construct a legal regime around different data types and/ or uses. For example, Personal Data Protection Law, Open Data Law (open by default), Freedom of Information Act, legal right to be protected from automated decision-making, and legal right to data portability.
In addition, it is necessary to be adaptable for the government as the governing bodies alter institutional structures in response to data-driven transformation. A good way to keep refining the approach is by incorporating feedback mechanisms that incorporate a multi-stakeholder perspective. Lastly, it is also important to regularly participate in the international efforts for establishing effective data governance rules.
India in the context of Data Governance
Based on the current state of global data governance, the United Kingdom had seemed to incorporate more aspects of data governance in their framework. It does not necessarily mean that it’s good, but it is simply that we do not know. That being said, the UK had more of the attributes than any other nation.
They have introduced several laws in the recent past including the Freedom of Information Act 2000, Data Protection Act, 2018, and The Data Protection, Privacy and Electronic Communications (EU Exit) Regulation 2020. When comparing to the other nations, India seems to be catching up with the current global standards, but it still has some areas to focus and improve upon.
Currently, the Personal Data Protection Bill in India is still pending. In fact, India was listed amongst the countries with the lowest composite scores of data governance. The scores are based on the dimensions of a comprehensive approach to data governance which states most and the least comprehensive based on the data governance metrics. The scale is out of 100, and the countries are measured and organized based on their overall points.
No one completely knows what comprehensive (or effective) data governance looks like. There is no formal program of data governance capacity building. The policymakers are just beginning to think about the spillover effects of data governance on their economy and on the achievement of other policy goals. As of the current state, there is significant convergence in personal data rules governing the public sector’s use of personal data. There has been a major convergence on the public data governance domain and there have also been some convergences on proprietary data governance.
This is only the first iteration and there are future additions that are planned in terms of both the indicators and countries covered. There will also be a website that will be created to showcase dimensions and results by categorized country. These results will be analyzed and compared along with regional, income, and other groupings. Lastly, the feedback mechanisms, indicators of proprietary data governance, measurable impact of data use, and re-use have to be further enhanced and developed.
In this final segment, Prof Aaronson answered the questions and points raised by the participants and the audience. The range of questions addressed includes topics such as, what would be an ideal measure of regulation in the domain of data governance when comparing countries like the United Kingdom? How do AI, blockchain, and other technologies enable data analysis and how can it aid in the act of data governance? How can India leverage the data governance architecture to become a thriving digital economy? After answering these questions, Dr Susan Aaronson put forth her closing remarks, upon which the webinar was concluded.
Acknowledgment: Dhimaan Sarkaar, (MS. Business Analytics – Loyola Marymount University, Los Angeles, CA) is a Research Intern at IMPRI.