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Querying the Semantic Web for Concept Identifiers to Annotate Research Datasets

Authors:
André Langer
Christoph Göpfert
Martin Gaedke

Keywords: Linked Data, Research Data Management, Data Publishing, FAIR, NFDI

Abstract:
Researchers are encouraged to describe and publish research datasets so that others can find and reuse it. Following a semantic approach, well-known concept identifiers are necessary that can be used as values for meta-data properties to describe relevant characteristics of such a research artifact. Multiple research disciplines, communities or initiatives have already created and published standardized terms as taxonomies or ontologies for that. However, these developments are distributed on the Web. As a consequence, it can be difficult for researchers to become aware of already recommended structured terminologies. Thus, they will further rely on ambiguous, literal annotations. In this paper, we investigate existing data sources in the Semantic Web that contain relevant terms to describe a research dataset in a structured, content-oriented and fine-grained way and how to integrate it in corresponding applications. We therefore analyze both Linked Data services and traditional terminology services on how to retrieve and filter terms for particular research-relevant characteristics. It is shown that a variety of well-structured community-specific terminologies with relevant concepts already exist, but that community-overspanning building blocks are nevertheless missing. Furthermore, filtering and mapping particular concepts is still a challenge to improve interdisciplinary publishing.

Pages: 49 to 55

Copyright: Copyright (c) IARIA, 2020

Publication date: October 25, 2020

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-61208-813-6

Location: Nice, France

Dates: from October 25, 2020 to October 29, 2020