Building Semantic Knowledge Graphs from (Semi-)Structured Data: A Review

Vetle Ryen, Ahmet Soylu and Dumitru Roman
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Vetle Ryen: Department of Informatics, University of Oslo, Gaustadalléen 23B, 0373 Oslo, Norway
Ahmet Soylu: Department of Computer Science, OsloMet—Oslo Metropolitan University, Pilestredet 35, 0167 Oslo, Norway
Dumitru Roman: Sustainable Communication Technologies, SINTEF AS, Forskningsveien 1, 0373 Oslo, Norway

Future Internet, 2022, vol. 14, issue 5, 1-24

Abstract: Knowledge graphs have, for the past decade, been a hot topic both in public and private domains, typically used for large-scale integration and analysis of data using graph-based data models. One of the central concepts in this area is the Semantic Web, with the vision of providing a well-defined meaning to information and services on the Web through a set of standards. Particularly, linked data and ontologies have been quite essential for data sharing, discovery, integration, and reuse. In this paper, we provide a systematic literature review on knowledge graph creation from structured and semi-structured data sources using Semantic Web technologies. The review takes into account four prominent publication venues, namely, Extended Semantic Web Conference , International Semantic Web Conference, Journal of Web Semantics , and Semantic Web Journal . The review highlights the tools, methods, types of data sources, ontologies, and publication methods, together with the challenges, limitations, and lessons learned in the knowledge graph creation processes.

Keywords: Semantic Web; linked data; knowledge graphs; structured data; semi-structured data (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
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