Comparative Analysis of Data Modeling Design Tools

Detalhes bibliográficos
Autor(a) principal: Carvalho, Gonçalo
Data de Publicação: 2022
Outros Autores: Mykolyshyn, Sergii, Cabral, Bruno, Bernardino, Jorge, Pereira, Vasco
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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spelling 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
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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
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