Indian government is taking bold steps to galvanise the data economy through open government data platforms, smart city initiatives, and legal means. Many players in the domain aspire to leverage the monetisation potential of untapped data silos. However, while industry practitioners and public authorities look to categorise their data assets for maximizing usefulness, they have limited know-how and limited understanding of the data flow ecosystem. The primary research question of interest in this paper, therefore, is to understand what the key existing data categories or taxonomies are to promote good data governance. To address the query, we systematically reviewed prior research from academia, public and legal administration, and industry reports. We found that data users classify their data assets to address five broad pre-requisites namely, regulatory / statutory compliance, technical requirements, sociocultural and operational responsibilities, risk mitigation, and corporate policies or voluntary criteria. As the next step we will investigate examples from the industry to illustrate and expand the five board archetypes in practice.
This paper is published by Rahul Patil and Prof Anjula Gurtoo of Centre for Society and Policy, Indian Institute of Science, Bangalore
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