An Adverse Event Reporting and Learning System for Water Sector Based on an Extension of the Eindhoven Classification Model

Detalhes bibliográficos
Autor(a) principal: Vicente, Henrique
Data de Publicação: 2015
Outros Autores: Borralho, Fábio, Couto, Catarina, Gomes, Guida, Alves, Victor, Neves, José
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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spelling 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).
publishDate 2015
dc.date.none.fl_str_mv 2015-10-09T16:07:29Z
2015-10-09
2015-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/15981
http://hdl.handle.net/10174/15981
https://doi.org/10.1007/s11269-015-1075-y
url http://hdl.handle.net/10174/15981
https://doi.org/10.1007/s11269-015-1075-y
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv 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
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Netherlands
publisher.none.fl_str_mv Springer Netherlands
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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repository.mail.fl_str_mv info@rcaap.pt
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