Provenance Ontology Model for Land Administration Spatial Data Supply Chains
Land Administration Spatial Data Supply Chains (SDSC) for state and territory jurisdictions in Australia require extensive investigation to address several contemporary issues and challenges that are hampering innovation and the use of spatial information across the land administration sector. The m...
| Main Authors: | , , , , |
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| Format: | Conference Paper |
| Published: |
http://ieeexplore.ieee.org/
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/11481 |
| _version_ | 1848747817602908160 |
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| author | Sadiq, Muhammad West, Geoff McMeekin, David Arnold, Lesley Moncrieff, Simon |
| author_facet | Sadiq, Muhammad West, Geoff McMeekin, David Arnold, Lesley Moncrieff, Simon |
| author_sort | Sadiq, Muhammad |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Land Administration Spatial Data Supply Chains (SDSC) for state and territory jurisdictions in Australia require extensive investigation to address several contemporary issues and challenges that are hampering innovation and the use of spatial information across the land administration sector. The management of cadastral data involves multiple value and supply chains. Each has heterogeneous geo-processes, methods, models and workflows that combine to generate, modify and deliver spatial data. The integration and processing of multiple datasets gives rise to end user questions about trust, quality, fitness for purpose, currency and authoritativeness of the data. This is because datasets originate from various sources, and different geo-processes are executed to deliver the final product. Understanding how data is collected, processed, managed and disseminated provides knowledge about its history, believability and provenance. This in turn increases the usability of data. This paper explores methods to capture spatial data provenance and data flow lineage. The aim is to develop a spatial data provenance model for the land administration domain using a comprehensive ontology. In the GeoPROV-LM model under development, all business and technical phases are defined and an extensive ontology structure developed using a semantic approach at the data flow level. |
| first_indexed | 2025-11-14T06:55:11Z |
| format | Conference Paper |
| id | curtin-20.500.11937-11481 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:55:11Z |
| publishDate | 2015 |
| publisher | http://ieeexplore.ieee.org/ |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-114812017-09-13T14:56:50Z Provenance Ontology Model for Land Administration Spatial Data Supply Chains Sadiq, Muhammad West, Geoff McMeekin, David Arnold, Lesley Moncrieff, Simon Land Administration Spatial Data Supply Chains (SDSC) for state and territory jurisdictions in Australia require extensive investigation to address several contemporary issues and challenges that are hampering innovation and the use of spatial information across the land administration sector. The management of cadastral data involves multiple value and supply chains. Each has heterogeneous geo-processes, methods, models and workflows that combine to generate, modify and deliver spatial data. The integration and processing of multiple datasets gives rise to end user questions about trust, quality, fitness for purpose, currency and authoritativeness of the data. This is because datasets originate from various sources, and different geo-processes are executed to deliver the final product. Understanding how data is collected, processed, managed and disseminated provides knowledge about its history, believability and provenance. This in turn increases the usability of data. This paper explores methods to capture spatial data provenance and data flow lineage. The aim is to develop a spatial data provenance model for the land administration domain using a comprehensive ontology. In the GeoPROV-LM model under development, all business and technical phases are defined and an extensive ontology structure developed using a semantic approach at the data flow level. 2015 Conference Paper http://hdl.handle.net/20.500.11937/11481 10.1109/INNOVATIONS.2015.7381537 http://ieeexplore.ieee.org/ restricted |
| spellingShingle | Sadiq, Muhammad West, Geoff McMeekin, David Arnold, Lesley Moncrieff, Simon Provenance Ontology Model for Land Administration Spatial Data Supply Chains |
| title | Provenance Ontology Model for Land Administration Spatial Data Supply Chains |
| title_full | Provenance Ontology Model for Land Administration Spatial Data Supply Chains |
| title_fullStr | Provenance Ontology Model for Land Administration Spatial Data Supply Chains |
| title_full_unstemmed | Provenance Ontology Model for Land Administration Spatial Data Supply Chains |
| title_short | Provenance Ontology Model for Land Administration Spatial Data Supply Chains |
| title_sort | provenance ontology model for land administration spatial data supply chains |
| url | http://hdl.handle.net/20.500.11937/11481 |