It is a long standing mantra in public policythat data and evidence driven policy making lead to better outcomes. But yearsof experience tells us this is easier said than done. Take the case of a healthsecretary of a state in India, trying to tackle the vexed issue of malnutrition.If she is data driven, it can take months of effort and many complex steps -from leveraging personal networks to access the right files from otherdepartments like food distribution, child welfare, and education; to getting adata entry operator to enter the information (which may be in PDF format, evenif it is "˜digitized'); to identifying researchers who can analyse the data andderive insights, and finally getting a consultant to help visualize and presentthe analysis in a compelling way to all stakeholders involved in decisionmaking.
These challenges in accessibility andusability of data are faced not just by government officials, but many otherswho use public datasets in their work. Companiescreating products and services for India's "˜nexthalf billion' internet users, needdemographic and socioeconomic population data to inform their marketpenetration strategy for different regions. A journalist tracking environment & climate change needs toaccess data from pollution control boards, the meteorological department,health, agriculture and public transport departments, then conduct analysisacross these different datasets to tell a better, more holistic story to informpublic opinion.
Forall these different types of users of government data, large volumes of richdatasets are in fact, technically "˜available' - but rarely accessible in aformat that is useful for analysis. Even highly sophisticated policy researchersspend significant time and resources to request access to datasets or downloadthem, only to find that they are in unwieldy formats. Every researcher has tothen repeat the same task of converting thesedatasets to machine readable formats, cleaning, organizing and codifying datato prepare it for analysis.
In this context it is heartening to see that NITI Aayog, the "˜think-tank' of the Government of India, has developed a vision to transform India's open data architecture. The stated ambition of NITI Aayog's National Data and Analytics Platform (NDAP) is to "serve as a single point for accessing data across all Ministry(ies) of Government of India combined with intuitive visualization and self-service analytics"