A Knowledge Graph-Based Data Integration Workflow for NFDI4Culture and Beyond
Despite covering specific scientific disciplines, all NFDI consortia share similar concepts such as organizations, people, institutions, areas of expertise, data repositories, projects, data sets, and research (meta)data, just to name a few. When interconnected, such information has the potential to open up new research horizons. To achieve this, however, the data needs to be available as linked open data (LOD). Hence a comprehensive workflow, which includes data discovery, harvesting, preprocessing, mapping, and integration into a knowledge graph is required, which is the topic of the present work.
Institutions
- Karlsruhe Institute of Technology (DE)
- FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE)
- Academy of Sciences and Literature (DE)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-11-18
- DOI
- https://doi.org/10.5281/zenodo.14181347
- Primary Topic
- Research Data Management Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00