The SHRUG is an open data platform describing multidimensional socioeconomic development across 600,000 villages and towns in India. This paper presents three illustrative analyses only possible with high-resolution data. First, it confirms that nighttime lights are highly significant proxies for population, employment, per capita consumption, and electrification at very local levels. However, elasticities between night-lights and these variables are far lower in time series than in cross section, and vary widely across context and level of aggregation. Next, this study shows that the distribution of manufacturing employment across villages follows a power law: the majority of rural Indians have considerably less access to manufacturing employment than is suggested by aggregate data. Third, a poverty mapping exercise explores local heterogeneity in living standards and estimates the potential targeting improvement from allocating programs at the village—rather than at the district—level. The SHRUG can serve as a model for open high-resolution data in developing countries.

Knowledge is a critical enabling factor for healthy agri-food innovation systems (AIS). AIS and related knowledge management (KM) frameworks face significant implementation challenges. We review applications of KM to AIS, the current state of the art and shortcomings and present a new KM framework, Agricultural Knowledge Management for Innovation (AKM4I). Previous agricultural KM frameworks do not integrate innovation pragmatically, use linear, reductionist, top-down pathways to innovation, and do not explicitly incorporate issues of power, politics, ownership, and trust when combining scientific and local knowledge across multiple stakeholders. The AKM4I framework addresses systemic interactions favouring innovation outcomes by formalising flows and management of information and knowledge between diverse sets of stakeholders; and explicitly considering previously unresolved practical and relational barriers aiming to facilitate more equitable, rapidly evolving, and actionable knowledge generation and management for innovation and transformational change. An agricultural case study serves as an example of the implementation of AKM4I.

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The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

In 2012, Africa RISING conducted participatory community analysis (PCA) as the first phase of a participatory development approach in the Ethiopian highlands. The PCA identified trends, constraints, and opportunitiesand shed light upon how farmers perceive livelihoods to be changing. Inputs, diseases, pests, soil fertility, post-harvest management, and fodder shortages were seen as challenges, while off-farm income has become increasingly important. Gender differences in livestock and crop preferences for food security and income sources were observed. PCA established development priorities in a way that researchers may have approached differently or missed, providing research development priorities for Africa RISING scientists.