An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2015 |
| Outros Autores: | , , , , |
| Tipo de documento: | Artigo |
| Idioma: | por |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | http://hdl.handle.net/10174/15981 https://doi.org/10.1007/s11269-015-1075-y |
Resumo: | The International Water Association and the World Health Organization has promoted, worldwide, the implementation of Water Safety Plans (WSPs) to ensure, consistently and systematically the water quality for human consumption. In order to complement and potentiate the WSPs, this work presents an adverse event reporting and learning system that may help to prevent hazards and risks. The proposed framework will allow for automatic knowledge extraction and report generation, in order to identify the most relevant causes of error. It will cater for the delineation of advance strategies to problem accomplishment, concluding about the impact, place of occurrence, form or type of event recorded with respect to the entities that operate in the water sector. To respond to this challenge the Eindhoven Classification Model was extended and adapted to the water industry, and used to classify the root causes of adverse events. Logic programming was used as a knowledge representation and reasoning mechanism, allowing one to model the universe of discourse in terms of defective data, information and knowledge, and its embedded quality, that enables a direct study of the event'sroot causes. Other approaches to address specific issues of water industry, presented in literature, do not consider the problem from a perspective of having to deal with incomplete, unknown, contradictory or even forbidden data, information or knowledge, and their conclusions are not object of a formal proof. Here it is not only presented a solution to the problem, but also a proof that the solution(s) is (are) the only one(s). |
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An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification ModelWater IndustryEindhoven Classification ModelKnowledge Representation and ReasoningLogic ProgrammingQuality of InformationThe International Water Association and the World Health Organization has promoted, worldwide, the implementation of Water Safety Plans (WSPs) to ensure, consistently and systematically the water quality for human consumption. In order to complement and potentiate the WSPs, this work presents an adverse event reporting and learning system that may help to prevent hazards and risks. The proposed framework will allow for automatic knowledge extraction and report generation, in order to identify the most relevant causes of error. It will cater for the delineation of advance strategies to problem accomplishment, concluding about the impact, place of occurrence, form or type of event recorded with respect to the entities that operate in the water sector. To respond to this challenge the Eindhoven Classification Model was extended and adapted to the water industry, and used to classify the root causes of adverse events. Logic programming was used as a knowledge representation and reasoning mechanism, allowing one to model the universe of discourse in terms of defective data, information and knowledge, and its embedded quality, that enables a direct study of the event'sroot causes. Other approaches to address specific issues of water industry, presented in literature, do not consider the problem from a perspective of having to deal with incomplete, unknown, contradictory or even forbidden data, information or knowledge, and their conclusions are not object of a formal proof. Here it is not only presented a solution to the problem, but also a proof that the solution(s) is (are) the only one(s).Springer Netherlands2015-10-09T16:07:29Z2015-10-092015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/15981http://hdl.handle.net/10174/15981https://doi.org/10.1007/s11269-015-1075-yporVicente, H., Borralho, F., Couto, C., Gomes, G., Alves, V. & Neves, J., An Adverse Event Reporting and Learning System for Water Sector based on an Extension of the Eindhoven Classification Model. Water Resources Management, 29 (14): 4927–4943, 2015.4927–49430920-4741 (Print)1573-1650 (Electronic)http://link.springer.com/article/10.1007%2Fs11269-015-1075-y29 (14)Water Resources ManagementDQUIhvicente@uevora.ptfabi0_jmb@hotmail.comhorbite@gmail.commguida.mgomes@gmail.comvalves@di.uminho.ptjneves@di.uminho.ptVicente, HenriqueBorralho, FábioCouto, CatarinaGomes, GuidaAlves, VictorNeves, Joséinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T19:02:15Zoai:dspace.uevora.pt:10174/15981Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:07:24.141696Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| title |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| spellingShingle |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model Vicente, Henrique Water Industry Eindhoven Classification Model Knowledge Representation and Reasoning Logic Programming Quality of Information |
| title_short |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| title_full |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| title_fullStr |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| title_full_unstemmed |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| title_sort |
An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model |
| author |
Vicente, Henrique |
| author_facet |
Vicente, Henrique Borralho, Fábio Couto, Catarina Gomes, Guida Alves, Victor Neves, José |
| author_role |
author |
| author2 |
Borralho, Fábio Couto, Catarina Gomes, Guida Alves, Victor Neves, José |
| author2_role |
author author author author author |
| dc.contributor.author.fl_str_mv |
Vicente, Henrique Borralho, Fábio Couto, Catarina Gomes, Guida Alves, Victor Neves, José |
| dc.subject.por.fl_str_mv |
Water Industry Eindhoven Classification Model Knowledge Representation and Reasoning Logic Programming Quality of Information |
| topic |
Water Industry Eindhoven Classification Model Knowledge Representation and Reasoning Logic Programming Quality of Information |
| description |
The International Water Association and the World Health Organization has promoted, worldwide, the implementation of Water Safety Plans (WSPs) to ensure, consistently and systematically the water quality for human consumption. In order to complement and potentiate the WSPs, this work presents an adverse event reporting and learning system that may help to prevent hazards and risks. The proposed framework will allow for automatic knowledge extraction and report generation, in order to identify the most relevant causes of error. It will cater for the delineation of advance strategies to problem accomplishment, concluding about the impact, place of occurrence, form or type of event recorded with respect to the entities that operate in the water sector. To respond to this challenge the Eindhoven Classification Model was extended and adapted to the water industry, and used to classify the root causes of adverse events. Logic programming was used as a knowledge representation and reasoning mechanism, allowing one to model the universe of discourse in terms of defective data, information and knowledge, and its embedded quality, that enables a direct study of the event'sroot causes. Other approaches to address specific issues of water industry, presented in literature, do not consider the problem from a perspective of having to deal with incomplete, unknown, contradictory or even forbidden data, information or knowledge, and their conclusions are not object of a formal proof. Here it is not only presented a solution to the problem, but also a proof that the solution(s) is (are) the only one(s). |
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2015 |
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2015-10-09T16:07:29Z 2015-10-09 2015-01-01T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://hdl.handle.net/10174/15981 http://hdl.handle.net/10174/15981 https://doi.org/10.1007/s11269-015-1075-y |
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http://hdl.handle.net/10174/15981 https://doi.org/10.1007/s11269-015-1075-y |
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por |
| language |
por |
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Vicente, H., Borralho, F., Couto, C., Gomes, G., Alves, V. & Neves, J., An Adverse Event Reporting and Learning System for Water Sector based on an Extension of the Eindhoven Classification Model. Water Resources Management, 29 (14): 4927–4943, 2015. 4927–4943 0920-4741 (Print) 1573-1650 (Electronic) http://link.springer.com/article/10.1007%2Fs11269-015-1075-y 29 (14) Water Resources Management DQUI hvicente@uevora.pt fabi0_jmb@hotmail.com horbite@gmail.com mguida.mgomes@gmail.com valves@di.uminho.pt jneves@di.uminho.pt |
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openAccess |
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Springer Netherlands |
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Springer Netherlands |
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