Automatic geospatial data conflation using semantic web technologies
Copyright 2016 ACM.A Spatial Data Supply Chain (SDSC) is a series of processes that convert raw spatial data (e.g. road locations) into useable products (e.g. road networks). Duplicate SDSCs are not uncommon across Australia. There exists data duplication between local government authorities, State/...
| Main Authors: | , , , , |
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| Format: | Conference Paper |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/53829 |
| _version_ | 1848759238415876096 |
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| author | Yu, F. West, Geoff Arnold, L. McMeekin, David Moncrieff, Simon |
| author_facet | Yu, F. West, Geoff Arnold, L. McMeekin, David Moncrieff, Simon |
| author_sort | Yu, F. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Copyright 2016 ACM.A Spatial Data Supply Chain (SDSC) is a series of processes that convert raw spatial data (e.g. road locations) into useable products (e.g. road networks). Duplicate SDSCs are not uncommon across Australia. There exists data duplication between local government authorities, State/Territory government departments and commonwealth agencies. To improve the SDSC process, this research explores data conflation as a means of removing the need for duplicate data handling in SDSCs. The research is studying how Semantic Web Technologies can be used to automate the conflation process. The approach focuses on building ontologies for spatial datasets and creating relevant rules based on geometry, topology, and policies. By satisfying these rules through a computer reasoning process, relevant datasets can be intelligently linked and integrated. The conflated dataset can then be used as the single authoritative and trusted source of data that is fit for multiple purposes. In this way the data can be co-maintained and used by multiple organizations eliminating the need for siloed SDSCs. |
| first_indexed | 2025-11-14T09:56:42Z |
| format | Conference Paper |
| id | curtin-20.500.11937-53829 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:56:42Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-538292017-09-13T15:47:35Z Automatic geospatial data conflation using semantic web technologies Yu, F. West, Geoff Arnold, L. McMeekin, David Moncrieff, Simon Copyright 2016 ACM.A Spatial Data Supply Chain (SDSC) is a series of processes that convert raw spatial data (e.g. road locations) into useable products (e.g. road networks). Duplicate SDSCs are not uncommon across Australia. There exists data duplication between local government authorities, State/Territory government departments and commonwealth agencies. To improve the SDSC process, this research explores data conflation as a means of removing the need for duplicate data handling in SDSCs. The research is studying how Semantic Web Technologies can be used to automate the conflation process. The approach focuses on building ontologies for spatial datasets and creating relevant rules based on geometry, topology, and policies. By satisfying these rules through a computer reasoning process, relevant datasets can be intelligently linked and integrated. The conflated dataset can then be used as the single authoritative and trusted source of data that is fit for multiple purposes. In this way the data can be co-maintained and used by multiple organizations eliminating the need for siloed SDSCs. 2016 Conference Paper http://hdl.handle.net/20.500.11937/53829 10.1145/2843043.2843375 restricted |
| spellingShingle | Yu, F. West, Geoff Arnold, L. McMeekin, David Moncrieff, Simon Automatic geospatial data conflation using semantic web technologies |
| title | Automatic geospatial data conflation using semantic web technologies |
| title_full | Automatic geospatial data conflation using semantic web technologies |
| title_fullStr | Automatic geospatial data conflation using semantic web technologies |
| title_full_unstemmed | Automatic geospatial data conflation using semantic web technologies |
| title_short | Automatic geospatial data conflation using semantic web technologies |
| title_sort | automatic geospatial data conflation using semantic web technologies |
| url | http://hdl.handle.net/20.500.11937/53829 |