Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164177
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dc.contributor.authorAkroyd, Jethroen_US
dc.contributor.authorHarper, Zacharyen_US
dc.contributor.authorSoutar, Daviden_US
dc.contributor.authorFarazi, Ferozen_US
dc.contributor.authorBhave, Amiten_US
dc.contributor.authorMosbach, Sebastianen_US
dc.contributor.authorKraft, Markusen_US
dc.date.accessioned2023-01-09T01:55:29Z-
dc.date.available2023-01-09T01:55:29Z-
dc.date.issued2022-
dc.identifier.citationAkroyd, J., Harper, Z., Soutar, D., Farazi, F., Bhave, A., Mosbach, S. & Kraft, M. (2022). Universal digital twin: land use. Data-Centric Engineering, 3(1), e3-1-e3-28. https://dx.doi.org/10.1017/dce.2021.21en_US
dc.identifier.issn2632-6736en_US
dc.identifier.urihttps://hdl.handle.net/10356/164177-
dc.description.abstractThis article develops an ontological description of land use and applies it to incorporate geospatial information describing land coverage into a knowledge-graph-based Universal Digital Twin. Sources of data relating to land use in the UK have been surveyed. The Crop Map of England (CROME) is produced annually by the UK Government and was identified as a valuable source of open data. Formal ontologies to represent land use and the geospatial data arising from such surveys have been developed. The ontologies have been deployed using a high-performance graph database. A customized vocabulary was developed to extend the geospatial capabilities of the graph database to support the CROME data. The integration of the CROME data into the Universal Digital Twin is demonstrated in two use cases that show the potential of the Universal Digital Twin to share data across sectors. The first use case combines data about land use with a geospatial analysis of scenarios for energy provision. The second illustrates how the Universal Digital Twin could use the land use data to support the cross-domain analysis of flood risk. Opportunities for the extension and enrichment of the ontologies, and further development of the Universal Digital Twin are discussed.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.relation.ispartofData-Centric Engineeringen_US
dc.rights© The Author(s), 2022. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleUniversal digital twin: land useen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen_US
dc.contributor.organizationCambridge Centre for Advanced Research and Education in Singapore (CARES)en_US
dc.identifier.doi10.1017/dce.2021.21-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85124689417-
dc.identifier.issue1en_US
dc.identifier.volume3en_US
dc.identifier.spagee3-1en_US
dc.identifier.epagee3-28en_US
dc.subject.keywordsCrop Mapen_US
dc.subject.keywordsDigital Twinen_US
dc.description.acknowledgementThis research was supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. Part of the research was also funded by Data-Centric Engineering e3-23 https://doi.org/10.1017/dce.2021.21 Published online by Cambridge University Press the European Commission, Horizon 2020 Programme, DOME 4.0 Project, GA 953163. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Part of this work was supported by Towards Turing 2.0 under the EPSRC Grant EP/W037211/1 & The Alan Turing Institute.en_US
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