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Quality metrics to measure the standards conformance of geospatial linked data

Yaman, Beyza, Thompson, Kevin and Brennan, Rob orcid logoORCID: 0000-0001-8236-362X (2020) Quality metrics to measure the standards conformance of geospatial linked data. In: 19th International Semantic Web Conference (ISWC 2020), 1-6 Nov 2020, Athens, Greece (Online).

Abstract
This paper describes three new Geospatial Linked Data (GLD) quality metrics that help evaluate conformance to standards. Standards conformance is a key quality criteria, for example for FAIR data. The metrics were implemented in the open source Luzzu quality assessment framework and used to evaluate four public geospatial datasets that showed a wide variation in standards conformance. This is the first set of Linked Data quality metrics developed specifically for GLD
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Proceedings of the ISWC 2020 Demos and Industry Tracks: From Novel Ideas to Industrial Practice co-located with 19th International Semantic Web Conference (ISWC 2020). .
Official URL:http://ceur-ws.org/Vol-2721/paper526.pdf
Copyright Information:© 2020 The Authors (CC-BY-4.0)
Funders:European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 801522, Science Foundation Ireland and co-funded by the European Regional Development Fund through the ADAPT Centre for Digital Content Technology [grant number 13/RC/2106], Ordnance Survey Ireland
ID Code:25391
Deposited On:19 Jan 2021 11:53 by Vidatum Academic . Last Modified 19 Jan 2021 11:53
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