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Advancing cross-domain data integration for global development - learnings from the WorldFAIR project
Many research disciplines, including social sciences, have strong traditions of sharing and integrating data within their discipline, to address complex, multifaceted research and policy questions. This integration however becomes more challenging however when there is a need for coordination across research domains - data, semantics, computation and research methods vary widely, making shared understanding between researchers difficult to achieve, particularly in the short term. The problem becomes even more challenging when machine-to-machine interoperability is required - humans are able to manage uncertainty far more readily than machines.
To this end, recent ongoing efforts by CODATA, the Committee on Data of the International Science Council, have focussed on addressing these cross-domain challenges through the initiative "Making Data Work for Cross-Domain Grand Challenges". As part of this program, CODATA, the Research Data Alliance and international partners across 11 different research domains have come together through the EU-funded WorldFAIR project to understand and progress cross-domain interoperability. The project aims to join up disconnected initiatives on data management, data stewardship, and FAIR data practices, within and across disciplines and internationally, by utilising eleven case studies of FAIR data management practices within and between domains.
This panel will present the first findings from three of these domain case studies, in social science and related domains of population health and urban health. Panellists from each of the case studies will present an overview of the first outputs of the project, studying current FAIR practices in each domain, and recommendations for future practice. The panel will then conclude with an introduction to the Cross-Domain Interoperability Framework - the key cross-domain output of the WorldFAIR project, which aims to establish key principles for a shared domain-agnostic framework for machine-to-machine interoperability across the research community as a whole.