Toward FAIR Semantic Publishing of Research Dataset Metadata in the Open Research Knowledge Graph
Raia Abu Ahmad, Jennifer D'Souza, Matth\"aus Zloch, Wolfgang Otto,, Georg Rehm, Allard Oelen, Stefan Dietze, S\"oren Auer

TL;DR
This paper introduces a semantic framework within the Open Research Knowledge Graph to improve the discoverability and FAIRness of research dataset metadata by integrating dataset descriptions with scholarly publications.
Contribution
It proposes the ORKG-Dataset content type, a standardized semantic model for research datasets linked with publications, enhancing transparency and discoverability.
Findings
Semantic model applied to 40 research datasets
Improved dataset discoverability through FAIR principles
Enhanced integration of datasets with scholarly publications
Abstract
Search engines these days can serve datasets as search results. Datasets get picked up by search technologies based on structured descriptions on their official web pages, informed by metadata ontologies such as the Dataset content type of schema.org. Despite this promotion of the content type dataset as a first-class citizen of search results, a vast proportion of datasets, particularly research datasets, still need to be made discoverable and, therefore, largely remain unused. This is due to the sheer volume of datasets released every day and the inability of metadata to reflect a dataset's content and context accurately. This work seeks to improve this situation for a specific class of datasets, namely research datasets, which are the result of research endeavors and are accompanied by a scholarly publication. We propose the ORKG-Dataset content type, a specialized branch of the Open…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSemantic Web and Ontologies · Data Quality and Management · Research Data Management Practices
