Bridging metadata gaps for FAIR multidisciplinary data access in Virtual Research Environments - Insights from Blue-Cloud2026 and FAIR-EASE

With Virtual Research Environments (VRE) and digital twins getting more and more common to support multidisciplinary Open Science, there is an ever growing need for the clear discovery and accessibility of data from different domains, FAIR for humans and machines. However, FAIR data and services are not yet the standard. Each domain, and within the domain the different research and data infrastructures, have different API’s, different metadata models, and semantics in place. In order to support multidisciplinary case studies, we need to succeed to bridge the gaps between these different domain-specific (meta)data standards and provide the scientists with a harmonised way of finding, accessing and processing this varying (meta)data.  This can be done in several ways:

• By creating a common metadata profile, suitable for machine-to-machine communication, to publish (bottom up!) the information about the data access service and the metadata of the datasets, taking also into account domain specific semantics (e.g. to describe parameters, units, etc). Such practices and standards should be tested and afterwards promoted widely, e.g. supported by EOSC. 
• Since the above profile is not yet implemented, except parts in certain subdomains, syntactic and semantic brokers need to be deployed to harmonise the various models into a central system with its own universal target model.
• By bringing the various metadata, via brokering, into one place this offers the opportunity to validate and check the metadata for completeness and suitability. Reports can be created to feed back FAIRness levels and improvements to the data publishers.

In this session, several promising activities will be presented related to work done in the Blue-Cloud2026 (marine) and FAIR-EASE (multi-disciplinary) projects, with all activities focusing on use cases requiring data access in a VRE and being linked to EOSC. The activities include:

• Set-up of a FAIR-EASE RDF Metadata model (DCAT-FE) to describe multi- disciplinary (meta)data uniformly, aiming to bridge the gaps between domain-specific (meta)data standards. 
• Development of an (Interdisciplinary) Data Discovery and Access Service ((I)DDAS) based on CNR’s Data Access Broker (DAB) that maps the harvested metadata into an ISO19139 target model, including domain specific vocabularies in order to provide harmonized discovery and access. 
• Reports and semantic analyser: Using the DAB as a broker the various metadata models and their content can be analysed for completeness and existence of semantics via a built in reporting service. Within FAIR-EASE NOC-BODC has developed a semantic analyser that checks for the existence of vocabulary terms, even if not expressed as such in the metadata.

The above work has much overlap with thematics at EOSC level where there are similar challenges in providing data access to the large variety of datasets in the data infrastructures. Both the Blue-Cloud2026 and FAIR-EASE teams are involved in EOSC Task Forces, Opportunity Area working groups and RDA to further promote results and support EOSC in solving this challenge.