Scientific studies of climate and meteorology focusing on India show significant increase in the variability and frequency of extreme precipitation events. The increased variability of weather patterns places a huge constraint on farmer’s ability to make strategic agricultural practice decisions. In response, public and private agro-met information services disseminate agro-met information to farmers. Yet, studies still show that there are constraints related to access and understanding of the information. An agro-met information service is based on scientific input from meteorology coupled with agricultural information and this information package is disseminated to farmers. Based on a study in three villages in Maharashtra, India, we show that the relevance of agro-met information differs depending on the decision-making situation. Several factors play an important role in farmer’s agricultural decision-making. The usefulness of the agro-met information from farmer perspectives depends on the access, salience, and credibility of the information. Some subscribers complained about the credibility and the salience of services, while others painted a more positive picture of the service, arguing that there was value in receiving such information. The subscribers mainly valued agro-met information for the ability to undertake precautionary actions. We found that agricultural decision-making was discussed in different arenas; these arenas represented possibilities for farmers to contextualize agro-met information and thereby translate information to timely and appropriate actions suited to the specific local context.

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This paper examines the socially responsible research and innovation aspects of a project that aimed to test various information communication technology-enabled tools and methods for crowdsourcing data on urban environmental challenges and measures. Using the responsible research and innovation (RRI) framework as a point of departure and analytical lens, this paper considers “socially responsible crowdsourcing” an iterative and recursive process of inclusion, anticipation, reflexivity, and responsiveness. RRI is increasingly being requested in publicly funded projects involving disruptive technologies; however, a response to this demand requires more studies on RRI field practices. This paper discusses the benefits, challenges, and contextual factors associated with the application of RRI to a research project on crowdsourcing in particular and to RRI-based projects in general. The paper indicates the need for incorporating a variety of skills and forging stronger cooperation between government entities and researchers. Moreover, based on the results of three case studies, three types of responsiveness in RRI practice were identified. They are incorporation, mutual learning, and discontinuation.