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Linked data schemata: fixing unsound foundations

Feeney, Kevin, Brennan, Rob orcid logoORCID: 0000-0001-8236-362X and Mendel-Gleason, Gavin orcid logoORCID: 0000-0002-1572-9756 (2017) Linked data schemata: fixing unsound foundations. Semantic Web, 9 (1). pp. 53-75. ISSN 1570-0844

Abstract
This paper describes our tools and method for an evaluation of the practical and logical implications of combining common linked data vocabularies into a single local logical model for the purpose of reasoning or performing quality evaluations. These vocabularies need to be unified to form a combined model because they reference or reuse terms from other linked data vocabularies and thus the definitions of those terms must be imported. We found that strong interdependencies between vocabularies are common and that a significant number of logical and practical problems make this model unification inconsistent. In addition to identifying problems, this paper suggests a set of recommendations for linked data ontology design best practice. Finally we make some suggestions for improving OWL’s support for distributed authoring and ontology reuse.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Linked Data; Reasoning; Data Quality
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Publisher:IOS Press
Official URL:http://dx.doi.org/10.3233/SW-170271
Copyright Information:© 2017 IOS
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:European Union’s Horizon 2020 research and innovation programme under grant agreement No 644055, ALIGNED project (www.aligned-project.eu), ADAPT Centre for Digital Content Technology, funded under the SFI Research Centres Programme (Grant 13/RC/2106) and co-funded by the European Regional Development Fund
ID Code:22976
Deposited On:15 Feb 2019 13:04 by Thomas Murtagh . Last Modified 17 Jan 2023 12:41
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