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The use of data across disiplinary boundaries is a challenge at many levels, but in order for researchers to make sense of often-unfamiliar data, they must be provided with a wealth of information regarding the provenance, methodology, structure, and semantics of data. Historically, such information has been modelled and implemented in different ways within different scientific domains. Approaches to geo-spatial data are especially problematic when we consider disiplines such as Environmental Science and Social Science. Recent work on cross-domain exchange of such metadata suggests that there are ways to improve this situation, making it far easier to support collaborative research. The EOSC "Climate Neutral and Smart Cities" project has demonstrated how improved tools for describing provenance and data processing could be developed for researchers, based on existing metadata standards such as DDI Lifecycle and DDI Cross-Domain Integration (DDI-CDI). Some of the same standards - notably DDI-CDI - are also at the core of an emerging framework designed to address the needs of cross-domain FAIR data exchange. This framework, the Cross-Domain Inteoperability Framework (CDIF) , is being developed through the WorldFAIR project, which looks at eleven different domain use cases. It exemplifies the kind of interoperability framework recommended by the EC's "Turning FAIR into Reality" report (doi: 10.2777/1524). Collaborative research involving environmental, climate, and social data is increasingly relevant as we try to understand how our world is changing, and what policies will best help us to address these changes. Aligning our data management and documentation systems on emerging best practice will make this collaborative research easier and more effective, helping us to understand the issues we face.
Arofan Gregory (Fri,) studied this question.