Task areas

Our overall aim is to provide RDM services to small independent labs and conceptually exchange with institutions and  excellence clusters to enable them for FAIR RDM. We are developing and implementing FAIR digital objects (FDOs) in our disciplinary communities in close collaboration with international RDM experts, primarily as organized in Fair Digital Objects Forum (FDO Forum) . We are contributing towards establishing FDOs as an open standard. FDOs are the equivalent to specific objects in the real world.  Our transdisciplinary agenda – based on a firm disciplinary foundation – will feedback to the forum.

Our consortium has seven structured task areas. Central for a sustainable RDM are FAIR Laboratories where we observe Local Structures for data production and management as well as Canonical Workflows providing a global link for labs and (meta-)data via Federated Repositories. Pivotal for proper semantic structures are ontologies which are relevant both for metadata as well as terminology. Both these aspects are observed within our task area Metadate and Ontologies. It is especially important to provide a consistent terminology service across disciplines which is inherent to our consortium due to its transdisciplinary agenda. Data Quality needs to be ensured before, during, and after data production. Our task area Quality Criteria and  Standards observes these needs. Evolving Infrastructures are defined, developed, and provided for both current as well as future RDM. Especially, we are concerned with Q-RDM for and eventually on quantum computers where Artificial Intelligence, AI, will augment and enable classical Computing. Community Interactions with our nine domains are provided via three channels. Domain and task area leaders work together to run paradigmatic use cases in Domains. Information flows into the communities by providing Data Literacy training, and out of the community via Surveys. Finally, the last task area provides Governance.

  1. FAIR Laboratory (Local Structures, Canonical Workflows)
  2. Metadata and Ontologies
  3. Federated Repositories
  4. Quality Criteria and Standards
  5. Evolving Infrastructure (Q-RDM, Q-AI, Q-Quality, Computing)  
  6. Data Literacy
  7. Community Interactions (Surveys, Template, Domains)
  8. Governance (Speaker, Monitoring, Communications)