Multi-criteria site selection using an ontology: the OntoZoning ontology of zones, land uses and programmes for Singapore
Abstract
Data related to urban planning is diverse both in terms of sources and formats. To facilitate urban analyses and public access to regulatory information, greater data interoperability is needed. Semantic web technologies, which use ontologies to link diverse data, are a promising solution to this problem. In this paper, we describe OntoZoning, an ontology representing relationships between zoning types, land uses and programmes (more specific land uses) in Singapore. We link the ontology to geospatial data stored in a knowledge graph, which allows executing multi-domain queries on urban data. We demonstrate how such queries can improve access to urban data, and in particular facilitate site selection and exploration. These are common tasks in urban planning and urban development processes. We also discuss how certain parts of zoning regulations are difficult to represent through ontologies, and would likely need to be defined more explicitly to fully represent city planning knowledge digitally. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000550962Publication status
publishedJournal / series
Cambridge Centre for Computational Chemical EngineeringVolume
Publisher
Computational Modelling GroupSubject
Urban development; city planning; Master plan; land use; zoning; ontology; knowledge graph; Semantic web; Web Ontology Language; Semantic City Planning Systems; South East AsiaOrganisational unit
08058 - Singapore-ETH Centre (SEC) / Singapore-ETH Centre (SEC)
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yes
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