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Data Interoperability

Data Interoperability

 

One important objective for OSCs is to enhance support for research that addresses the fundamental challenges of our age (including global sustainability, disaster risk reduction and so on). Such research topics often require an interdisciplinary approach and the ability to combine data from across traditional domain boundaries. Many OSCs explicitly aim to support and enhance the services provided by established Research Infrastructures, while also seeking to break down the silos that may inhibit data sharing and interoperability.

The FAIR principles provide a framework for convergence and a number of topics can usefully be addressed to pursue alignment and interoperability among OSCs. These include but are not limited to: the emerging FAIR Digital Object Framework; the use of structural and provenance metadata to facilitate machine-actionability across data; and the alignment and development of good practice for semantic artefacts (including scientific vocabularies). The EOSC Interoperability Framework may provide a good starting point for discussions around how to align and how OSCs can contribute and engage with global efforts to address the I (interoperability) and the R (reusability) of FAIR.

Working Group Co-chairs

Pascal Heus, Metadata Technology North America, Canada

Milan Ostersek, European Open Science Cloud

Christine Kirkpatrick, San Diego Supercomputing Center

Natasha Simons, Australian research Data Commons

 

Secretariat Contact

Simon Hodson, CODATA

Lianglin HU, CNIC

 

Additional participants are invited: sign-up here, if interested to join the WG.