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 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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