Social Sciences & Humanities

Challenge

The broader SSH field features different community specific services to manage the wide variety of metadata, data types and tools required to serve the diverse application scenarios in this extremely hectic domain. Examples are: the CLARIN’s Language Resource Switchboard, enabling discovery of tools to manage language resources of different types, the CLARIN Virtual Collection Registry used by scientists to create “shareable and citablet set of links to digital objects” the CLARIN Digital Object Gateway (DOG), a meta-resolver for PIDs across different CLARIN repository types and PID schemas (e.g. DOIs, Handles and GLAM object IDs from Europeana). Making such services available and interoperable with similar services from different domains would favour cross-discipline alignment in service development, mitigate redundancy and ultimately facilitate the realisation of “horizontal” services across sciences.

Case study description

In this case study CLARIN will integrate its DOG, the CLARIN Virtual Collection Registry and the Language Resource Switchboard with the EOSC MSCR, the EOSC DTR and the EOSC PIDMR in order to (i) make their functions and content available beyond the SSH Cluster borders to all EOSC users, (ii) benefit from the services and content (e.g. data types, crosswalks) available from other communities and infrastructures via the EOSC MSCR and DTR. Moreover, the integration with EOSC registries will make CLARIN domain language data resources available via the EOSC PIDGraph and the EOSC RDGraph. The CLARIN Virtual Collection Registry will indirectly benefit from this integration, relying on common PID frameworks, sharing of crosswalks and schemas.

Expected impact

Overall the discoverability of language data hosted in the CLARIN domain is improved through use of the proposed EOSC MSCR and Graph components, improving options for reuse of the data and its augmentation with other relevant data from other sources - for instance by inclusion in virtual collections. This effort will also lead to faster and easier processing of language data that is referred to with a persistent identifier.