A strategy for visual structural data analysis of labor accident data
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFU |
Texto Completo: | https://repositorio.ufu.br/handle/123456789/28282 http://doi.org/10.14393/ufu.di.2019.2578 |
Resumo: | Labor accidents are a serious social problem that results in damages to employees, employers, and governments, also consuming a significant portion of the World's GDP. In Brazil, The Brazilian Federal Labor Prosecution Office is the institutional service responsible for the defense of worker rights, and among its functions is the supervision and control of labor health and safety. They collect data on labor accidents in Brazilian territory and provide an anonymized version of this data publicly. This process generates a large volume of data containing important strategical information, which is often not straightforward to be extracted with manual analysis. Information visualization is a research area that studies the creation of visual representations for abstract structured or non-structured data, aiming to help people execute tasks more effectively. We propose a computational strategy employing a combination of Information Visualization techniques to perform a visual analysis of labor accident data, while not being restricted to this scenario. We developed a system that implements our strategy, and is comprised of two complementary visualizations, i) a multidimensional projection layout + a political map, and ii) a treemap layout + a parallel sets layout. We performed several exploratory analysis, in order to exploit the visualizations' complementary capacities in providing simultaneous analysis of different data aspects. We obtained interesting results, identifying profiles associated with small/large geographical areas, similarities among geographically distant localities, occurrence patterns related to cities' size and economic development, the frequency distribution of labor accident types in Brazil, and characterized labor accidents in terms of occupation type, gender differences, causer agent, among other aspects. We believe that the proposed strategy facilitates and enhances the analysis of labor accident data, providing effective and efficient means to help governments to evaluate current public policies and foment the creation of new ones to reduce labor accidents and grant safety to employees, and also encourage transparency in governments and citizen participation. |
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A strategy for visual structural data analysis of labor accident dataUma estratégia para análise estruturais visuais de dados de acidentes de trabalhoAcidente de TrabalhoDados GovernamentaisVisualização da InformaçãoLabor AccidentGovernmental DataInformation VisualizationCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOLabor accidents are a serious social problem that results in damages to employees, employers, and governments, also consuming a significant portion of the World's GDP. In Brazil, The Brazilian Federal Labor Prosecution Office is the institutional service responsible for the defense of worker rights, and among its functions is the supervision and control of labor health and safety. They collect data on labor accidents in Brazilian territory and provide an anonymized version of this data publicly. This process generates a large volume of data containing important strategical information, which is often not straightforward to be extracted with manual analysis. Information visualization is a research area that studies the creation of visual representations for abstract structured or non-structured data, aiming to help people execute tasks more effectively. We propose a computational strategy employing a combination of Information Visualization techniques to perform a visual analysis of labor accident data, while not being restricted to this scenario. We developed a system that implements our strategy, and is comprised of two complementary visualizations, i) a multidimensional projection layout + a political map, and ii) a treemap layout + a parallel sets layout. We performed several exploratory analysis, in order to exploit the visualizations' complementary capacities in providing simultaneous analysis of different data aspects. We obtained interesting results, identifying profiles associated with small/large geographical areas, similarities among geographically distant localities, occurrence patterns related to cities' size and economic development, the frequency distribution of labor accident types in Brazil, and characterized labor accidents in terms of occupation type, gender differences, causer agent, among other aspects. We believe that the proposed strategy facilitates and enhances the analysis of labor accident data, providing effective and efficient means to help governments to evaluate current public policies and foment the creation of new ones to reduce labor accidents and grant safety to employees, and also encourage transparency in governments and citizen participation.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorDissertação (Mestrado)Acidentes de trabalho são um problema social sério, que causa danos para empregados, empregadores, e governos, consumindo uma parcela significativa do PIB mundial. No Brasil, o Ministério Público do Trabalho é o órgão institucional responsável pela defesa dos direitos dos trabalhadores, e entre as suas funções estão a supervisão e controle da saúde e segurança no trabalho. Eles coletam dados sobre acidentes de trabalho no Brasil e disponibilizam esses dados publicamente. Esse processo gera um grande volume de dados contendo informações estratégicas importantes, geralmente difíceis de extrair por meio de análises manuais. Visualização da informação é uma área de pesquisa que estuda a criação de representações visuais para dados, visando ajudar pessoas a executarem tarefas mais eficientemente. Propomos uma estratégia que emprega técnicas de visualização da informação para analisar dados de acidentes de trabalho, sem ser restrita a este cenário. Desenvolvemos um sistema que implementa essa estratégia, e que compreende duas visualizações complementares, i) projeção multidimensional + mapa político, e ii) treemap + conjuntos paralelos. Realizamos diversas análises exploratórias aproveitando as capacidades complementares das visualizações em prover análise simultânea de diferentes aspectos dos dados. Identificamos perfis associados a áreas geográficas pequenas/grandes, similaridades entre localidades geograficamente distantes, padrões de ocorrência relacionados ao tamanho e desenvolvimento econômico das cidades, a distribuição de frequência dos tipos de acidentes de trabalho no Brasil, e os caracterizamos em termos de tipo de ocupação, diferenças de gênero, agente causador, entre outros aspectos. Cremos que a estratégia proposta facilita e melhora a análise de dados de acidentes de trabalho, provendo meios eficazes e eficientes para ajudar governos a avaliar políticas atuais e fomentar a criação de novas políticas para reduzir acidentes de trabalho e garantir segurança para empregados, e também encorajar a transparência em governos e a participação popular.Universidade Federal de UberlândiaBrasilPrograma de Pós-graduação em Ciência da ComputaçãoPaiva, José Gustavo de Souzahttp://lattes.cnpq.br/4981210260282182Carneiro, Murillo Guimarãeshttp://lattes.cnpq.br/8158868389973535Meiguins, Bianchi Seriquehttp://lattes.cnpq.br/3032638002357978Rodrigues, Mateus Pinto2020-01-13T12:13:39Z2020-01-13T12:13:39Z2019-11-27info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfRODRIGUES, Mateus Pinto. A strategy for visual structural data analysis of labor accident data. 2019. 86 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Uberlândia, Uberlândia, 2019. DOI http://dx.doi.org/10.14393/ufu.di.2019.2578.https://repositorio.ufu.br/handle/123456789/28282http://doi.org/10.14393/ufu.di.2019.2578enghttp://creativecommons.org/licenses/by-sa/3.0/us/info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFUinstname:Universidade Federal de Uberlândia (UFU)instacron:UFU2020-01-14T06:10:53Zoai:repositorio.ufu.br:123456789/28282Repositório InstitucionalONGhttp://repositorio.ufu.br/oai/requestdiinf@dirbi.ufu.bropendoar:2020-01-14T06:10:53Repositório Institucional da UFU - Universidade Federal de Uberlândia (UFU)false |
dc.title.none.fl_str_mv |
A strategy for visual structural data analysis of labor accident data Uma estratégia para análise estruturais visuais de dados de acidentes de trabalho |
title |
A strategy for visual structural data analysis of labor accident data |
spellingShingle |
A strategy for visual structural data analysis of labor accident data Rodrigues, Mateus Pinto Acidente de Trabalho Dados Governamentais Visualização da Informação Labor Accident Governmental Data Information Visualization CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
title_short |
A strategy for visual structural data analysis of labor accident data |
title_full |
A strategy for visual structural data analysis of labor accident data |
title_fullStr |
A strategy for visual structural data analysis of labor accident data |
title_full_unstemmed |
A strategy for visual structural data analysis of labor accident data |
title_sort |
A strategy for visual structural data analysis of labor accident data |
author |
Rodrigues, Mateus Pinto |
author_facet |
Rodrigues, Mateus Pinto |
author_role |
author |
dc.contributor.none.fl_str_mv |
Paiva, José Gustavo de Souza http://lattes.cnpq.br/4981210260282182 Carneiro, Murillo Guimarães http://lattes.cnpq.br/8158868389973535 Meiguins, Bianchi Serique http://lattes.cnpq.br/3032638002357978 |
dc.contributor.author.fl_str_mv |
Rodrigues, Mateus Pinto |
dc.subject.por.fl_str_mv |
Acidente de Trabalho Dados Governamentais Visualização da Informação Labor Accident Governmental Data Information Visualization CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
topic |
Acidente de Trabalho Dados Governamentais Visualização da Informação Labor Accident Governmental Data Information Visualization CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
description |
Labor accidents are a serious social problem that results in damages to employees, employers, and governments, also consuming a significant portion of the World's GDP. In Brazil, The Brazilian Federal Labor Prosecution Office is the institutional service responsible for the defense of worker rights, and among its functions is the supervision and control of labor health and safety. They collect data on labor accidents in Brazilian territory and provide an anonymized version of this data publicly. This process generates a large volume of data containing important strategical information, which is often not straightforward to be extracted with manual analysis. Information visualization is a research area that studies the creation of visual representations for abstract structured or non-structured data, aiming to help people execute tasks more effectively. We propose a computational strategy employing a combination of Information Visualization techniques to perform a visual analysis of labor accident data, while not being restricted to this scenario. We developed a system that implements our strategy, and is comprised of two complementary visualizations, i) a multidimensional projection layout + a political map, and ii) a treemap layout + a parallel sets layout. We performed several exploratory analysis, in order to exploit the visualizations' complementary capacities in providing simultaneous analysis of different data aspects. We obtained interesting results, identifying profiles associated with small/large geographical areas, similarities among geographically distant localities, occurrence patterns related to cities' size and economic development, the frequency distribution of labor accident types in Brazil, and characterized labor accidents in terms of occupation type, gender differences, causer agent, among other aspects. We believe that the proposed strategy facilitates and enhances the analysis of labor accident data, providing effective and efficient means to help governments to evaluate current public policies and foment the creation of new ones to reduce labor accidents and grant safety to employees, and also encourage transparency in governments and citizen participation. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-27 2020-01-13T12:13:39Z 2020-01-13T12:13:39Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
RODRIGUES, Mateus Pinto. A strategy for visual structural data analysis of labor accident data. 2019. 86 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Uberlândia, Uberlândia, 2019. DOI http://dx.doi.org/10.14393/ufu.di.2019.2578. https://repositorio.ufu.br/handle/123456789/28282 http://doi.org/10.14393/ufu.di.2019.2578 |
identifier_str_mv |
RODRIGUES, Mateus Pinto. A strategy for visual structural data analysis of labor accident data. 2019. 86 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Uberlândia, Uberlândia, 2019. DOI http://dx.doi.org/10.14393/ufu.di.2019.2578. |
url |
https://repositorio.ufu.br/handle/123456789/28282 http://doi.org/10.14393/ufu.di.2019.2578 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-sa/3.0/us/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-sa/3.0/us/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Uberlândia Brasil Programa de Pós-graduação em Ciência da Computação |
publisher.none.fl_str_mv |
Universidade Federal de Uberlândia Brasil Programa de Pós-graduação em Ciência da Computação |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFU instname:Universidade Federal de Uberlândia (UFU) instacron:UFU |
instname_str |
Universidade Federal de Uberlândia (UFU) |
instacron_str |
UFU |
institution |
UFU |
reponame_str |
Repositório Institucional da UFU |
collection |
Repositório Institucional da UFU |
repository.name.fl_str_mv |
Repositório Institucional da UFU - Universidade Federal de Uberlândia (UFU) |
repository.mail.fl_str_mv |
diinf@dirbi.ufu.br |
_version_ |
1805569688536612864 |