To objective of this priority activity is ‘making data work for cross-domain grand challenges’. This means addressing issues of interoperability and reusability (the relatively neglected I and R of FAIR) in the context of cross-domain research and most importantly, those international scientific activities that are a priority for ISC (including but not limited to climate change mitigation and adaptation, the sustainability science and the SDGs, disaster risk reduction, and measures of human development). This is an important and distinct role for CODATA as an extension of the ISC executive and in support of the ISC mission.
The premise is that the major, pressing global scientific and human issues of the 21st century can only be addressed through research that works across disciplines to understand complex systems, and which uses a transdisciplinary approach to turn data into knowledge and then into action. The initiative has its roots in preparatory work that was part of the first ISC Action Plans. The EC-funded WorldFAIR project enabled CODATA to accelerate this initiative, through a case study-led methodology and the use of FAIR Implementation Profiles. The major, highly impactful outputs of WorldFAIR were a set of Policy Recommendations and the Cross-Domain Interoperability Framework (CDIF).
The flagship activity of ‘Making Data Work…’ is now WorldFAIR+, a ground-breaking initiative to provide practical guidance and technical recommendations to ensure that the data needed for interdisciplinary research is FAIR.
Other CODATA activities under the banner of ‘Making Data Work…’ includes work on FAIR Vocabularies, the Global Open Science Cloud (GOSC) initiative, and work on topics of fundamental importance such as the Digital Representation of Units of Measure (DRUM).
The impact of this work will be to empower interdisciplinary research for grand challenge issues, by improving science systems’ capacity to combine data and metadata across domains, and ensuring that ISC’s Science Missions for sustainability are supported by good data practices.