Querying and visualisation of semantic data
Main Author: | |
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Publication Date: | 2023 |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10773/41758 |
Summary: | Semantic technologies can describe data, map, and link distributed datasets for people and machines. Over the years, many semantic data repositories have been made available on the web. However, this has created new challenges regarding exploiting these resources efficiently. Usually, querying services use formal query languages requiring knowledge beyond the standard user’s expertise, which is critical in adopting semantic solutions. Several proposals to overcome this difficulty have suggested using question-answering systems that provide user-friendly interfaces allowing natural language inputs. On the other hand, processing and integrating the results in the usual tabular forms does not help to understand the retrieved information better. This thesis proposes solutions and methods to facilitate access and retrieval of information in the context of semantic data repositories. A first contribution concerns the proposal of a strategy for creating and publishing semantic data for different application domains, emphasising biomedical data. A second contribution proposes a new method to access semantic data using natural language as input. Finally, several possibilities for visualising semantic data to facilitate their understanding and exploitation are analysed. The proposals were validated considering use cases in the biomedical domain using data and metadata from patients with Alzheimer’s and patients with Huntington’s disease. |
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Querying and visualisation of semantic dataSemantic webSemantic dataLinked dataKnowledge basesFAIR dataNatural language interfacesQuestion-answeringData visualisationSemantic technologies can describe data, map, and link distributed datasets for people and machines. Over the years, many semantic data repositories have been made available on the web. However, this has created new challenges regarding exploiting these resources efficiently. Usually, querying services use formal query languages requiring knowledge beyond the standard user’s expertise, which is critical in adopting semantic solutions. Several proposals to overcome this difficulty have suggested using question-answering systems that provide user-friendly interfaces allowing natural language inputs. On the other hand, processing and integrating the results in the usual tabular forms does not help to understand the retrieved information better. This thesis proposes solutions and methods to facilitate access and retrieval of information in the context of semantic data repositories. A first contribution concerns the proposal of a strategy for creating and publishing semantic data for different application domains, emphasising biomedical data. A second contribution proposes a new method to access semantic data using natural language as input. Finally, several possibilities for visualising semantic data to facilitate their understanding and exploitation are analysed. The proposals were validated considering use cases in the biomedical domain using data and metadata from patients with Alzheimer’s and patients with Huntington’s disease.As tecnologias semânticas podem descrever dados, mapear e vincular conjuntos de dados distribuídos para uso por pessoas e máquinas. Ao longo dos anos, muitos repositórios de dados semânticos foram disponibilizados na web. No entanto, isso criou novos desafios no que diz respeito à exploração desses recursos de forma eficiente. Normalmente, os serviços de consulta usam linguagens de consulta formais que exigem conhecimento além da experiência do utilizador padrão, o que é crítico na adoção de soluções semânticas. Várias propostas para superar essa dificuldade vêm sugerindo o uso de sistemas pergunta resposta que fornecem interfaces amigáveis, permitindo entradas em linguagem natural. Por outro lado, processar e integrar os resultados nas formas tabulares usuais não ajuda a entender melhor as informações recuperadas. Esta tese propõe soluções e métodos para facilitar o acesso e recuperação de informação no contexto de repositórios de dados semânticos. Uma primeira contribuição diz respeito à proposta de uma estratégia de criação e publicação de dados semânticos para diferentes domínios de aplicação, com ênfase em dados biomédicos. Uma segunda contribuição propõe um novo método para aceder aos dados semânticos usando linguagem natural como entrada. Por fim, analisam-se várias possibilidades de visualização de dados semânticos para facilitar sua compreensão e exploração. As propostas foram validadas considerando casos de uso no domínio biomédico usando dados e metadados de pacientes com Alzheimer e pacientes com doença de Huntington.2024-04-30T12:39:47Z2023-03-23T00:00:00Z2023-03-23doctoral thesisinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10773/41758engPereira, Arnaldo António Pintoinfo: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:RCAAP2024-05-06T04:57:02Zoai:ria.ua.pt:10773/41758Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:24:24.652245Repositórios 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 |
Querying and visualisation of semantic data |
title |
Querying and visualisation of semantic data |
spellingShingle |
Querying and visualisation of semantic data Pereira, Arnaldo António Pinto Semantic web Semantic data Linked data Knowledge bases FAIR data Natural language interfaces Question-answering Data visualisation |
title_short |
Querying and visualisation of semantic data |
title_full |
Querying and visualisation of semantic data |
title_fullStr |
Querying and visualisation of semantic data |
title_full_unstemmed |
Querying and visualisation of semantic data |
title_sort |
Querying and visualisation of semantic data |
author |
Pereira, Arnaldo António Pinto |
author_facet |
Pereira, Arnaldo António Pinto |
author_role |
author |
dc.contributor.author.fl_str_mv |
Pereira, Arnaldo António Pinto |
dc.subject.por.fl_str_mv |
Semantic web Semantic data Linked data Knowledge bases FAIR data Natural language interfaces Question-answering Data visualisation |
topic |
Semantic web Semantic data Linked data Knowledge bases FAIR data Natural language interfaces Question-answering Data visualisation |
description |
Semantic technologies can describe data, map, and link distributed datasets for people and machines. Over the years, many semantic data repositories have been made available on the web. However, this has created new challenges regarding exploiting these resources efficiently. Usually, querying services use formal query languages requiring knowledge beyond the standard user’s expertise, which is critical in adopting semantic solutions. Several proposals to overcome this difficulty have suggested using question-answering systems that provide user-friendly interfaces allowing natural language inputs. On the other hand, processing and integrating the results in the usual tabular forms does not help to understand the retrieved information better. This thesis proposes solutions and methods to facilitate access and retrieval of information in the context of semantic data repositories. A first contribution concerns the proposal of a strategy for creating and publishing semantic data for different application domains, emphasising biomedical data. A second contribution proposes a new method to access semantic data using natural language as input. Finally, several possibilities for visualising semantic data to facilitate their understanding and exploitation are analysed. The proposals were validated considering use cases in the biomedical domain using data and metadata from patients with Alzheimer’s and patients with Huntington’s disease. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-03-23T00:00:00Z 2023-03-23 2024-04-30T12:39:47Z |
dc.type.driver.fl_str_mv |
doctoral thesis |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/41758 |
url |
http://hdl.handle.net/10773/41758 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
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RCAAP |
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RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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info@rcaap.pt |
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