Ontology modeling for a drought management information system
Thailand suffers from frequent flooding during the monsoon season and droughts in summer. In some places, severe cases of both may even occur. Managing water resources effectively requires a good information system for decision-making. There is currently a lack in knowledge sharing between organizat...
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sg-ntu-dr.10356-1542352021-12-22T20:10:58Z Ontology modeling for a drought management information system Kaewboonma, Nattapong Tuamsuk, Kulthida Buranarach, Marut Library and information science Thailand suffers from frequent flooding during the monsoon season and droughts in summer. In some places, severe cases of both may even occur. Managing water resources effectively requires a good information system for decision-making. There is currently a lack in knowledge sharing between organizations and researchers responsible. These are the experts in monitoring and controlling the water supply and its conditions. The knowledge owned by these experts are not captured, classified and integrated into an information system for decision-making. Ontologies are formal knowledge representation models. Knowledge management and artificial intelligence technology is a basic requirement for developing ontology-based semantic search on the Web. In this paper, we present ontology modeling approach that is based on the experiences of the researchers. The ontology for drought management consists of River Basin Ontology, Statistics Ontology and Task Ontology to facilitate semantic match during search. The hybrid ontology architecture can also be used for drought management. Published version 2021-12-16T04:32:27Z 2021-12-16T04:32:27Z 2014 Journal Article Kaewboonma, N., Tuamsuk, K. & Buranarach, M. (2014). Ontology modeling for a drought management information system. Library and Information Science Research E-Journal, 24(1), 21-33. https://dx.doi.org/10.32655/LIBRES.2014.1.3 1058-6768 https://hdl.handle.net/10356/154235 10.32655/LIBRES.2014.1.3 1 24 21 33 en Library and Information Science Research E-Journal © 2014 Nattapong Kaewboonma, Kulthida Tuamsuk, Marut Buranarach. All rights reserved. application/pdf |
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Library and information science Kaewboonma, Nattapong Tuamsuk, Kulthida Buranarach, Marut Ontology modeling for a drought management information system |
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Thailand suffers from frequent flooding during the monsoon season and droughts in summer. In some places, severe cases of both may even occur. Managing water resources effectively requires a good information system for decision-making. There is currently a lack in knowledge sharing between organizations and researchers responsible. These are the experts in monitoring and controlling the water supply and its conditions. The knowledge owned by these experts are not captured, classified and integrated into an information system for decision-making. Ontologies are formal knowledge representation models. Knowledge management and artificial intelligence technology is a basic requirement for developing ontology-based semantic search on the Web. In this paper, we present ontology modeling approach that is based on the experiences of the researchers. The ontology for drought management consists of River Basin Ontology, Statistics Ontology and Task Ontology to facilitate semantic match during search. The hybrid ontology architecture can also be used for drought management. |
format |
Article |
author |
Kaewboonma, Nattapong Tuamsuk, Kulthida Buranarach, Marut |
author_facet |
Kaewboonma, Nattapong Tuamsuk, Kulthida Buranarach, Marut |
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Kaewboonma, Nattapong |
title |
Ontology modeling for a drought management information system |
title_short |
Ontology modeling for a drought management information system |
title_full |
Ontology modeling for a drought management information system |
title_fullStr |
Ontology modeling for a drought management information system |
title_full_unstemmed |
Ontology modeling for a drought management information system |
title_sort |
ontology modeling for a drought management information system |
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2021 |
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https://hdl.handle.net/10356/154235 |
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1720447100884353024 |