Chapter 1 reveals how India’s statistical infrastructure was built and establishes its link to planning. It tracks the early career of P. C. Mahalanobis and the institution he founded in Calcutta (the Indian Statistical Institute) to describe the ascent of statistics as an academic discipline in India, and its growing association with applied economics. This was the period that produced organizations such as the Central Statistical Organization and the National Sample Survey, both of which persist and remain significant to policy making to this day. It was also during this phase that India first began periodic assessments of national income (a precursor to the GDP) and nationwide sample surveys that delivered high-definition snapshots of the economy. The chapter argues that this national statistical framework—pioneering among developing nations and a global trailblazer in large sample surveys—emerged as a response to the quantitative needs of centralized economic planning.

‘Community resource directory data' comprises information about the accessibility of health, human, and social services that are available to people in need. Such services are provided by a fractured landscape of governments, nonprofit organizations, contractors, and other civic institutions. Institutions that fund services don’t tend to collect information about the accessibility of those services – and service providers often lack strong incentives to promote this information themselves. Instead, directory data tends to be aggregated by ‘infomediaries,’ for use in their proprietary channels, or for sale to third parties as a commodity. The result is a knowledge anti-commons, in which resource data is simultaneously overproduced and underutilized – a tragedy that causes systemic dysfunction across the so-called safety net. This paper outlines a set of strategic interventions pursued through the Open Referral Initiative – a community of practice that has developed data exchange standards, open source tools, and pilot projects through which multiple stakeholders experiment with new methods of sharing resource information as open data. The paper’s final section outlines a set of institutional designs that can hypothetically sustain the provision of trustworthy open resource data as a public good.