Comparative Analysis of Data Modeling Design Tools
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/100599 https://doi.org/10.1109/ACCESS.2021.3139071 |
Resumo: | Conceptual modeling describes the physical or social aspects of the world abstractly, encompassing the interpretation of data production, gathering, visualization, and analysis. The quality of the data analysis system will limit the excellence of any decision-making process. Thus, accurately specifying the physical data model is essential. The primary goal of our work is to compare tools that can create this physical model. We recognize several types of data models, but we only include the relational data model. We evaluate free and commercial data modeling tools. But it is challenging to decide how to compare them and which elements are crucial. We propose a new approach for software tools' evaluation based on the Business Readiness Rating (BRR) model and the OSSpal evaluation methodology. In this work, we show that this new methodology can be tailored to the needs of each individual developer or team, thus providing proper and meaningful results. Also, by applying this hybrid approach to the evaluation of data modelling tools, we show it can robustly handle the bias from lesser relevant evaluation categories. |
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Comparative Analysis of Data Modeling Design ToolsData modelingData modeling toolsDatabase management systemsDesign toolsConceptual modeling describes the physical or social aspects of the world abstractly, encompassing the interpretation of data production, gathering, visualization, and analysis. The quality of the data analysis system will limit the excellence of any decision-making process. Thus, accurately specifying the physical data model is essential. The primary goal of our work is to compare tools that can create this physical model. We recognize several types of data models, but we only include the relational data model. We evaluate free and commercial data modeling tools. But it is challenging to decide how to compare them and which elements are crucial. We propose a new approach for software tools' evaluation based on the Business Readiness Rating (BRR) model and the OSSpal evaluation methodology. In this work, we show that this new methodology can be tailored to the needs of each individual developer or team, thus providing proper and meaningful results. Also, by applying this hybrid approach to the evaluation of data modelling tools, we show it can robustly handle the bias from lesser relevant evaluation categories.2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/100599http://hdl.handle.net/10316/100599https://doi.org/10.1109/ACCESS.2021.3139071eng2169-3536Carvalho, GonçaloMykolyshyn, SergiiCabral, BrunoBernardino, JorgePereira, Vascoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-07-06T20:37:05Zoai:estudogeral.uc.pt:10316/100599Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:17:57.239801Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Comparative Analysis of Data Modeling Design Tools |
title |
Comparative Analysis of Data Modeling Design Tools |
spellingShingle |
Comparative Analysis of Data Modeling Design Tools Carvalho, Gonçalo Data modeling Data modeling tools Database management systems Design tools |
title_short |
Comparative Analysis of Data Modeling Design Tools |
title_full |
Comparative Analysis of Data Modeling Design Tools |
title_fullStr |
Comparative Analysis of Data Modeling Design Tools |
title_full_unstemmed |
Comparative Analysis of Data Modeling Design Tools |
title_sort |
Comparative Analysis of Data Modeling Design Tools |
author |
Carvalho, Gonçalo |
author_facet |
Carvalho, Gonçalo Mykolyshyn, Sergii Cabral, Bruno Bernardino, Jorge Pereira, Vasco |
author_role |
author |
author2 |
Mykolyshyn, Sergii Cabral, Bruno Bernardino, Jorge Pereira, Vasco |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Carvalho, Gonçalo Mykolyshyn, Sergii Cabral, Bruno Bernardino, Jorge Pereira, Vasco |
dc.subject.por.fl_str_mv |
Data modeling Data modeling tools Database management systems Design tools |
topic |
Data modeling Data modeling tools Database management systems Design tools |
description |
Conceptual modeling describes the physical or social aspects of the world abstractly, encompassing the interpretation of data production, gathering, visualization, and analysis. The quality of the data analysis system will limit the excellence of any decision-making process. Thus, accurately specifying the physical data model is essential. The primary goal of our work is to compare tools that can create this physical model. We recognize several types of data models, but we only include the relational data model. We evaluate free and commercial data modeling tools. But it is challenging to decide how to compare them and which elements are crucial. We propose a new approach for software tools' evaluation based on the Business Readiness Rating (BRR) model and the OSSpal evaluation methodology. In this work, we show that this new methodology can be tailored to the needs of each individual developer or team, thus providing proper and meaningful results. Also, by applying this hybrid approach to the evaluation of data modelling tools, we show it can robustly handle the bias from lesser relevant evaluation categories. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 |
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/10316/100599 http://hdl.handle.net/10316/100599 https://doi.org/10.1109/ACCESS.2021.3139071 |
url |
http://hdl.handle.net/10316/100599 https://doi.org/10.1109/ACCESS.2021.3139071 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2169-3536 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134074954055680 |