A user-centered process for the analysis and visualization of open data sets
- Autores
- Tejeda, Marcia; Torres, Diego
- Año de publicación
- 2020
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Open data is growing all the time throughout the world. Open government is advancing and more and more open data portals are available to be consulted by anyone. It is assumed that joining and combining two or more data sources can provide new information or knowledge that was not previously available. To be able to combine different datasets, the use of statistical and computer science techniques such as data mining and machine learning is suggested. Although this is a practice that is currently carried out by data science professionals, this work invites the community in general to be able to do it through a process centered on the user. This article presents a process and a web tool that implements the analysis and visualization process.
- Materia
-
Ciencias de la Computación e Información
Open-datasets
User centered Process
Data visualization - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/11359
Ver los metadatos del registro completo
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A user-centered process for the analysis and visualization of open data setsTejeda, MarciaTorres, DiegoCiencias de la Computación e InformaciónOpen-datasetsUser centered ProcessData visualizationOpen data is growing all the time throughout the world. Open government is advancing and more and more open data portals are available to be consulted by anyone. It is assumed that joining and combining two or more data sources can provide new information or knowledge that was not previously available. To be able to combine different datasets, the use of statistical and computer science techniques such as data mining and machine learning is suggested. Although this is a practice that is currently carried out by data science professionals, this work invites the community in general to be able to do it through a process centered on the user. This article presents a process and a web tool that implements the analysis and visualization process.2020-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/11359enginfo:eu-repo/semantics/altIdentifier/issn/1613-0073info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-04T09:43:49Zoai:digital.cic.gba.gob.ar:11746/11359Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-04 09:43:49.277CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
A user-centered process for the analysis and visualization of open data sets |
title |
A user-centered process for the analysis and visualization of open data sets |
spellingShingle |
A user-centered process for the analysis and visualization of open data sets Tejeda, Marcia Ciencias de la Computación e Información Open-datasets User centered Process Data visualization |
title_short |
A user-centered process for the analysis and visualization of open data sets |
title_full |
A user-centered process for the analysis and visualization of open data sets |
title_fullStr |
A user-centered process for the analysis and visualization of open data sets |
title_full_unstemmed |
A user-centered process for the analysis and visualization of open data sets |
title_sort |
A user-centered process for the analysis and visualization of open data sets |
dc.creator.none.fl_str_mv |
Tejeda, Marcia Torres, Diego |
author |
Tejeda, Marcia |
author_facet |
Tejeda, Marcia Torres, Diego |
author_role |
author |
author2 |
Torres, Diego |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias de la Computación e Información Open-datasets User centered Process Data visualization |
topic |
Ciencias de la Computación e Información Open-datasets User centered Process Data visualization |
dc.description.none.fl_txt_mv |
Open data is growing all the time throughout the world. Open government is advancing and more and more open data portals are available to be consulted by anyone. It is assumed that joining and combining two or more data sources can provide new information or knowledge that was not previously available. To be able to combine different datasets, the use of statistical and computer science techniques such as data mining and machine learning is suggested. Although this is a practice that is currently carried out by data science professionals, this work invites the community in general to be able to do it through a process centered on the user. This article presents a process and a web tool that implements the analysis and visualization process. |
description |
Open data is growing all the time throughout the world. Open government is advancing and more and more open data portals are available to be consulted by anyone. It is assumed that joining and combining two or more data sources can provide new information or knowledge that was not previously available. To be able to combine different datasets, the use of statistical and computer science techniques such as data mining and machine learning is suggested. Although this is a practice that is currently carried out by data science professionals, this work invites the community in general to be able to do it through a process centered on the user. This article presents a process and a web tool that implements the analysis and visualization process. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/11359 |
url |
https://digital.cic.gba.gob.ar/handle/11746/11359 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/1613-0073 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
reponame_str |
CIC Digital (CICBA) |
collection |
CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
institution |
CICBA |
repository.name.fl_str_mv |
CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
repository.mail.fl_str_mv |
marisa.degiusti@sedici.unlp.edu.ar |
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12.623145 |