Towards a Versatile Terminology Service for Empowering FAIR Research Data: Enabling Ontology Discovery, Design, Curation, and Utilization Across Scientific Communities

Abstract

To fully harness the potential of data, the creation of machine-readable data and utilization of the FAIR Data Principles is vital for successful data-driven science. Ontologies serve as the foundation for generating semantically rich, FAIR data that machines can understand, enabling seamless data integration and exchange across scientific disciplines. In this paper, we introduce a versatile Terminology Service that supports various tasks, including discovery, provision, as well as ontology design and curation. This service offers unified access to a vast array of ontologies across scientific disciplines, encouraging their reuse, improvement, and maturation. We present a user-driven service development approach, along with a use case involving a collaborative ontology design process, engaging domain experts, knowledge workers, and ontology engineers. This collaboration incorporates the application and evaluation of the Terminology Service, as well as supplementary tools, workflows, and collaboration models. We demonstrate the feasibility, prerequisites, and ongoing challenges related to developing Terminology Services that address numerous aspects of ontology utilization for producing FAIR, machine-actionable data.

Researcher or Crowd Member? Why not both! The Open Research Knowledge Graph for Applying and Communicating CrowdRE Research

“…The ORKG is a cross-domain research knowledge graph combining manual crowdsourcing and (semi-)automated approaches for the production, curation, and (re)use of FAIR scientific knowledge from publications, software, and datasets [6]- [9]. The TS is a cross-domain service that supports the discovery, provision, design, and curation of ontologies [10]. Based on the work of the task area Ellen 6 in NFDI4Ing, the ORKG integrated the TS that in turn curates the OEO, so that engineers can describe and organize scientific knowledge and data as so-called ORKG contributions.…”