Abstract
Controlled vocabularies, such as classification schemes, glossaries, taxonomies, or thesauri, play an important role in many Web services. One of the main areas of application of controlled vocabularies is the domain of information retrieval systems, as they can be used to improve the findability of resources. For instance, concepts described in a vocabulary may be used to uniquely classify resources, to tag them with relevant keywords, or to annotate them with domain-specific attributes. The Simple Knowledge Organization System (SKOS) is an established data model of the Semantic Web domain that can be used to describe vocabularies in a semantically structured format. However, modelling a vocabulary is oftentimes highly time demanding, labor-intensive, and requires both familiarity with basic Semantic Web technologies and expertise in the application domain. This complicates both the development of new vocabularies and the conversion of existing vocabularies into the RDF data model. We propose an intermediate, YAML-based format to express concepts and their relationships hierarchically. The intermediate format can be converted automatically into a SKOS vocabulary using a command-line conversion program. To demonstrate the feasibility of our approach, we selected 26 vocabularies of highly diverse formats, expressed them in the proposed intermediate format, which was subsequently converted in an automated manner into the corresponding SKOS vocabulary using our yaml2skos program. Our approach enables users with little to no familiarity with the Semantic Web to develop SKOS vocabularies, thereby lowering the barrier to participation in the Semantic Web landscape.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
References
Introduction to Controlled Vocabularies: Terminologies for Art, Architecture, and Other Cultural Works
The 2012 ACM Computing Classification System
Library of Congress Classification Outline - Classification - Cataloging and Acquisitions (Library of Congress)
Scriven, M.: Evaluation Thesaurus. Edgepress (1981)
Thesaurus: mass communication - UNESCO Digital Library
Gawron, V.J., et al.: Human factors taxonomy. In: Proceedings of the Human Factors Society Annual Meeting, vol. 35, pp. 1284–1287 (1991)
Gross, T., Taylor, A.: What have we got to lose? The effect of controlled vocabulary on keyword searching results. Coll. Res. Libr. (2005)
Gross, T., Taylor, A.G., Joudrey, D.N.: Still a lot to lose: the role of controlled vocabulary in keyword searching. Cat. Classif. Q. 53, 1–39 (2015)
van Assem, M., Menken, M.R., Schreiber, G., Wielemaker, J., Wielinga, B.: A method for converting thesauri to RDF/OWL. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 17–31. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30475-3_3
SWAD-Europe Thesaurus Activity: Deliverable 8.8 Migrating Thesauri to the Semantic Web
van Assem, M., Malaisé, V., Miles, A., Schreiber, G.: A method to convert thesauri to SKOS. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 95–109. Springer, Heidelberg (2006). https://doi.org/10.1007/11762256_10
Suominen, O., Hyvönen, E.: Improving the quality of SKOS vocabularies with skosify. In: ten Teije, A., et al. (eds.) EKAW 2012. LNCS (LNAI), vol. 7603, pp. 383–397. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33876-2_34
Vanhoefer, J., Matos, M., Pathirana, D., Schälte, Y., Hasenauer, J.: Yaml2sbml: human-readable and -writable specification of ODE models and their conversion to SBML. J. Open Source Softw. 6, 3215 (2021)
Assche, D.V., Delva, T., Heyvaert, P., Meester, B.D., Dimou, A.: Towards a more human-friendly knowledge graph generation & publication (2021)
Musen, M.A.: The protégé project: a look back and a look forward. AI Matt. 1, 4–12 (2015). https://doi.org/10.1145/2757001.2757003
Heyvaert, P., De Meester, B., Dimou, A., Verborgh, R.: Declarative rules for linked data generation at your fingertips! In: Gangemi, A., et al. (eds.) ESWC 2018. LNCS, vol. 11155, pp. 213–217. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98192-5_40
Mader, C., Haslhofer, B., Isaac, A.: Finding quality issues in SKOS vocabularies. In: Zaphiris, P., Buchanan, G., Rasmussen, E., Loizides, F. (eds.) TPDL 2012. LNCS, vol. 7489, pp. 222–233. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33290-6_25
Kitchenham, B.: Procedures for performing systematic reviews (2004)
Acknowledgement
The research was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 514664767—TRR 386.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Göpfert, C., Haas, J.I., Schröder, L., Gaedke, M. (2024). Streamlining Vocabulary Conversion to SKOS: A YAML-Based Approach to Facilitate Participation in the Semantic Web. In: Stefanidis, K., Systä, K., Matera, M., Heil, S., Kondylakis, H., Quintarelli, E. (eds) Web Engineering. ICWE 2024. Lecture Notes in Computer Science, vol 14629. Springer, Cham. https://doi.org/10.1007/978-3-031-62362-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-031-62362-2_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-62361-5
Online ISBN: 978-3-031-62362-2
eBook Packages: Computer ScienceComputer Science (R0)