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A SKOS taxonomy of the UN global geospatial information management data theme

Yaman, Beyza ORCID: 0000-0003-2130-0312, Thompson, Kevin and Brennan, Rob ORCID: 0000-0001-8236-362X (2021) A SKOS taxonomy of the UN global geospatial information management data theme. In: 4th International Workshop on Geospatial Linked Data at ESWC 2021, 6-10 June 2021, Hersonissos, Greece(Online). (In Press)

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Abstract

Complex data domains increase the difficulty of structuring, sharing, discovering and governing information. For the geospatial domain common models such as INSPIRE have been established in the European Union. The United Nations initiative on Global Geospatial Information Management (UN-GGIM) draws together national and regional capacities. Interoperability is the main principle behind these initiatives. Nonetheless there is a lack of published research to date on mapping agency geospatial linked data leveraging the UN-GGIM taxonomy of information management data themes. Thus, we have identified use cases and defined a Simple Knowledge Organization System (SKOS)\footnote{\url{https://www.w3.org/TR/skos-reference/}} taxonomy expressing the UN GGIM data themes for national spatial infrastructure. This has been applied in a metadata generation and reporting tool for Ordnance Survey Ireland (OSi) which underpinned improved governance and reporting infrastructure in OSi. This demonstrated the contribution of Semantic Web technology to spatial data governance as well as its importance for data publishing. This paper presents a documented open license SKOS taxonomy for the UN GGIM data themes that follows Linked Data best practices. It provides a set of three use cases, an overview of UN-GGIM theme definitions and an example application of the taxonomy for deployment in OSi for DCAT metadata generation and data publishing pipeline reporting.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Geospatial Linked Data,Data Themes, Data Catalog
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: 4th International Workshop on Geospatial Linked Data at ESWC 2021, Proceedings. . GeoLD2021.
Publisher:GeoLD2021
Official URL:https://dice-group.github.io/GeoLD2021/
Copyright Information:© 2021 The Authors
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:25927
Deposited On:14 Jun 2021 14:31 by Vidatum Academic . Last Modified 25 Nov 2021 16:15

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