Yaman, Beyza, Thompson, Kevin and Brennan, Rob ORCID: 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 Institutes 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 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
431kB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record