Yet our capacity for carrying out this kind of work is constrained by limitations in our ability to access and combine heterogeneous data from disparate disciplinary sources.
Addressing this shortcoming requires an ecosystem of resources that enable data to be FAIR (Findable, Accessible, Interoperable and Reusable) for humans and machines. Achieving this goal requires a major consensus-building effort, in particular to gain agreement about the core technologies and semantic solutions which will allow data to be combined for cross-domain research.
Towards this aim, CODATA, the ISC’s Committee on Data, is currently developing a decadal programme, ‘Making Data Work for Cross-Domain Grand Challenges’, to be launched at the ISC General Assembly in October 2021.
In 2020 CODATA developed a number of pilot activities which will be core to the programme. Prominent among these has been collaboration with the DDI (Data Documentation Initiative) Alliance on the review and refinement of a new metadata specification: DDI-Cross Domain Integration (CDI). This has included a European Open Science Cloud Co-Creation Project to explore a number of use cases and examples.
The programme is also exploring how to make vocabularies and terminologies FAIR. This has led to a set of recommendations ’Ten Simple Rules for making a vocabulary FAIR’ and a collaboration with IUSSP on FAIR Vocabularies in the demographic sciences.
The programme comprises case studies to explore the application of technologies and semantic solutions in various cross-domain research fields, including infectious diseases, disaster risk reduction and resilient and healthy cities. For infectious diseases, CODATA is a partner in the INSPIRE-PEACH project which is addressing the challenges of combining demographic health data, clinical data and phylogenetic tree data to support COVID-19 research in Africa.
Finally, CODATA has been preparing the Global Open Science Cloud (GOSC initiative) which will encourage cooperation and alignment between various Open Science platforms, including the European Open Science Cloud, the Malaysian Open Science Platform, the Chinese Science and Technology Cloud and so on. The initiative comprises a number of thematic Working Groups and Case Studies for data sharing and interoperability between platforms.