Database Federation for Spatial Digital Twins with Semantically Enhanced Data Processing: A use case of Mission Mjøsa
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| Publicado en: | The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences vol. XLVIII-2/W10-2025 (2025), p. 231 |
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| Otros Autores: | , , |
| Publicado: |
Copernicus GmbH
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 024 | 7 | |a 10.5194/isprs-archives-XLVIII-2-W10-2025-231-2025 |2 doi | |
| 035 | |a 3227542537 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 263042 |2 nlm | ||
| 100 | 1 | |a Ranatunga, Sajith |u NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway; NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway | |
| 245 | 1 | |a Database Federation for Spatial Digital Twins with Semantically Enhanced Data Processing: A use case of Mission Mjøsa | |
| 260 | |b Copernicus GmbH |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Developing spatial digital twins (SDTs) for inland water bodies requires addressing challenges such as temporal variability, dynamic water surface conditions, and heterogeneous water datasets. This study presents a semantic integration framework combining Ontology-Based Data Access (OBDA) with PostgreSQL database federation to support real-time decision-making in SDT applications. The framework integrates hydrological data, sensor networks, bathymetric data, and other static datasets under a unified ontology, enabling federated SPARQL queries without centralizing data. A 3D visualization interface allows interactive analysis of results from the SPARQL queries. Demonstrated through the Mission Mjøsa use case, this approach supports inland water mapping and decision support by aligning spatial data across domains. The framework offers a scalable solution for water data processing, semantic fusion, and scenario-based simulation, contributing to the development of intelligent, semantically enriched SDTs for sustainable environment management. | |
| 653 | |a Hydrologic data | ||
| 653 | |a Environmental management | ||
| 653 | |a Datasets | ||
| 653 | |a Semantics | ||
| 653 | |a Data processing | ||
| 653 | |a Spatial data | ||
| 653 | |a Temporal variations | ||
| 653 | |a Sustainability management | ||
| 653 | |a Queries | ||
| 653 | |a Water | ||
| 653 | |a Digital twins | ||
| 653 | |a Data analysis | ||
| 653 | |a Databases | ||
| 653 | |a Inland waters | ||
| 653 | |a Real time | ||
| 653 | |a Bathymetric data | ||
| 653 | |a Linked Data | ||
| 653 | |a Interoperability | ||
| 653 | |a Ontology | ||
| 653 | |a Initiatives | ||
| 653 | |a Water resources management | ||
| 653 | |a Relational data bases | ||
| 653 | |a Hydrology | ||
| 653 | |a Semantic web | ||
| 653 | |a Query formulation | ||
| 653 | |a Climate change | ||
| 653 | |a Water quality | ||
| 653 | |a Sensors | ||
| 653 | |a Decision making | ||
| 653 | |a Archives & records | ||
| 653 | |a Geographic information systems | ||
| 653 | |a Land use | ||
| 653 | |a Environmental monitoring | ||
| 653 | |a Pollution | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Rune Strand Ødegård |u NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway; NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway | |
| 700 | 1 | |a Onstein, Erling |u NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway; NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway | |
| 700 | 1 | |a Jetlund, Knut |u NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway; NTNU Gjøvik, Teknologiveien 22, 2815 Gjøvik, Norway; Kartverket, Kartverksveien 21, 3511 Hønefoss, Norway | |
| 773 | 0 | |t The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences |g vol. XLVIII-2/W10-2025 (2025), p. 231 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3227542537/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3227542537/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |