An end-user pipeline for scrapping and visualizing semi-structured data over the Web
- Autores
- Bosetti, Gabriela Alejandra; Firmenich, Sergio; Winckler, Marco; Rossi, Gustavo Héctor; Cornejo Fandos, Ulises; Egyed Zsigmond, Elöd
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets.
- Materia
-
Ciencias de la Computación e Información
Infovis
Web augmentation
Web scrapping - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/10709
Ver los metadatos del registro completo
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An end-user pipeline for scrapping and visualizing semi-structured data over the WebBosetti, Gabriela AlejandraFirmenich, SergioWinckler, MarcoRossi, Gustavo HéctorCornejo Fandos, UlisesEgyed Zsigmond, ElödCiencias de la Computación e InformaciónInfovisWeb augmentationWeb scrappingThe Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets.2019info: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/11746/10709enginfo:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-19274-7_17info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:39:53Zoai:digital.cic.gba.gob.ar:11746/10709Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:39:53.645CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
spellingShingle |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web Bosetti, Gabriela Alejandra Ciencias de la Computación e Información Infovis Web augmentation Web scrapping |
title_short |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_full |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_fullStr |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_full_unstemmed |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_sort |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
dc.creator.none.fl_str_mv |
Bosetti, Gabriela Alejandra Firmenich, Sergio Winckler, Marco Rossi, Gustavo Héctor Cornejo Fandos, Ulises Egyed Zsigmond, Elöd |
author |
Bosetti, Gabriela Alejandra |
author_facet |
Bosetti, Gabriela Alejandra Firmenich, Sergio Winckler, Marco Rossi, Gustavo Héctor Cornejo Fandos, Ulises Egyed Zsigmond, Elöd |
author_role |
author |
author2 |
Firmenich, Sergio Winckler, Marco Rossi, Gustavo Héctor Cornejo Fandos, Ulises Egyed Zsigmond, Elöd |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Ciencias de la Computación e Información Infovis Web augmentation Web scrapping |
topic |
Ciencias de la Computación e Información Infovis Web augmentation Web scrapping |
dc.description.none.fl_txt_mv |
The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets. |
description |
The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 |
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/11746/10709 |
url |
https://digital.cic.gba.gob.ar/handle/11746/10709 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-19274-7_17 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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application/pdf |
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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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score |
13.070432 |