Yaman, Beyza, Thompson, Kevin and Brennan, Rob ORCID: 0000-0001-8236-362X (2020) Standards conformance metrics for geospatial linked data. In: Second Iberoamerican Knowledge Graphs and Semantic Web Conference 2020, 26-27 Nov 2020, Merida, Yucatan. Mexico (Online). ISBN 978-3-030-65384-2
Abstract
This paper describes a set of new Geospatial Linked Data (GLD) quality metrics based on ISO and W3C spatial standards for monitoring geospatial data production. The Luzzu quality assessment framework was employed to implement the metrics and evaluate a set of five public geospatial datasets. Despite the availability of metrics-based quality assessment tools for Linked Data, there is a lack of dedicated quality metrics for GLD, as well as, no metrics were found based on geospatial data standards and best practices. This paper provides nine new metrics and a first assessment of public datasets for geospatial standards compliance. Our approach also demonstrates the effectiveness of developing new quality metrics through analysis of the requirements defined in relevant standards.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Subjects: | Computer Science > Machine learning |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > ADAPT |
Published in: | Knowledge Graphs and Semantic Web. Communications in Computer and Information Science 1232. Springer, Cham. ISBN 978-3-030-65384-2 |
Publisher: | Springer, Cham |
Official URL: | http://dx.doi.org/10.1007/978-3-030-65384-2_9 |
Copyright Information: | © 2020 Springer |
Funders: | European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 801522, cience 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: | 25392 |
Deposited On: | 19 Jan 2021 13:29 by Vidatum Academic . Last Modified 19 Jan 2021 13:29 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
360kB |
Metrics
Altmetric Badge
Dimensions Badge
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record