Talk of a data revolution is not hyperbole. The ease in which data relating to human behaviour and transactions can be gathered has led to new industries driven by their ability to elicit predictive and commercially advantageous information from masses of data. In academia, new data science courses and multidisciplinary centres are springing up to feed the demand for these analytical and data management skills. The data revolution, the phenomenon of Big Data and advances in data science are everywhere impacting both scientific research and industry. Exploiting the opportunities and addressing the challenges afforded by the data revolution and using them to generate wider societal benefit will fundamentally depend on the creation of a complementary ‘Open Data’ environment. Open data is crucial to the maintenance of scientific ‘self-correction’ whereby the data underlying published concepts are open to scrutiny, replication or invalidation. The rapid growth of data makes this crucial principle of research ever more difficult to sustain, and increasingly requires both the data and the code used in data analysis to be open, accessible and useable. Our response must include new technical solutions for presenting, sharing and analysing data; on capacity building in “data science”; and on changing the habits and norms of researchers and their institutions to create a culture of openness and data sharing. Science is an international activity, done in a national cultural setting, thereby requiring national strategies to fit within a common international frame. The role of international bodies such as CODATA and the International Council of Science is to facilitate the fit between national priorities and processes and rapidly developing international norms. To help address these issues, CODATA promotes Open Data and Open Science through three strategic priorities: 1) Supporting implementation of data principles, policies and practices 2) Addressing the frontiers of data science and its adaptation to scientific research. 3) Capacity building for data science (particularly in low and middle income countries - LMICs) This presentation will examine the context of the ‘Data Revolution’ and provide an introduction to CODATA’s analysis of these issues and activities in the priority areas identified. Particular emphasis will be placed on the policy environment, a holistic approach to capacity building and the research data skills that benefit various role in science systems.

Responses to the data revolution: CODATA on policy, data science, and capacity building

251st National Meeting (2016)

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