Semantic Co-Working Space for Collections: Infrastructure-supported Data Literacy and Data Science competence development with SODa and WissKI (CoRDI 2025)
Year: 2025
Type: article
Abstract: With the Semantic Co-Working Space (SCS), the joint project SODa (Sammlungen, Objekte, Datenkompetenzen - Collections, Objects and Data Competence) [1] is establishing a modular, scalable infrastructure for research, teaching and skills development in the field of research data management (RDM) and data-driven research. The focus is on digital work with collection data, which is supported by WissKI (Wissenschaftliche Kommunikationsinfrastruktur - Scientific Communication Infrastructure) [2], OpenRefine, Jupyter Notebooks, WebProtegé and various database systems. The technical infrastructure is operated on a long-term basis by the IGSD e.V. (Interessengemeinschaft für Semantische Datenverarbeitung e.V.) [3] and the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) [4]. The SCS and the accompanying training courses developed within the SODa project contribute to the RDM and data science community in two ways: Firstly, a robust, semantically sound infrastructure is provided that enables the context-rich collection and use of research data in line with the FAIR principles and ensures the sustainable storage of collection data. Secondly, educational programs will be implemented to provide users with concrete skills in dealing with digital tools, standards (e.g. CIDOC-CRM), data quality and sustainable storage. These offerings are continuously developed and communicated by the existing technical experts who provide advisory support. Author contributions Visualization – Julia NeubauerWriting – original draft – Robert Nasarek, Julia NeubauerWriting – review & editing – Kai Amann, Canan Hastik, Robert Nasarek, Julia Neubauer, Gudrun SchwenkProject administration – Mark Fichtner
Authors: Amann, Kai, Fichtner, Mark, Hastik, Canan, Nasarek, Robert, Neubauer, Julia, Schwenk, Gudrun Angelika
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7085000659
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