A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments

Autores
Buccella, Agustina; Cechich, Alejandra; Saurin, Federico; Montenegro, Ayelén; Rodríguez, Andrea; Muñoz, Angel
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data systems (BDSs) can be approached from different perspectives, all of them useful, depending on the objectives pursued. In particular, in this work, we address BDSs in the area of software engineering, contributing to the generation of novel methodologies and techniques for software reuse. In this article, we propose a methodology to develop reusable BDSs by mirroring activities from software product line engineering. This means that the process of building BDSs is approached by analyzing the variety of domain features and modeling them as a family of related assets. The contextual perspective of the proposal, along with its supporting tool, is introduced through a case study in the agrometeorology domain. The characterization of variables for frost analysis exemplifies the importance of identifying variety, as well as the possibility of reusing previous analyses adjusted to the profile of each case. In addition to showing interesting findings from the case, we also exemplify our concept of context variety, which is a core element in modeling reusable BDSs.
Fil: Buccella, Agustina. Universidad Nacional del Comahue. Facultad de Informatica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina
Fil: Cechich, Alejandra. Universidad Nacional del Comahue. Facultad de Informatica; Argentina
Fil: Saurin, Federico. Universidad Nacional del Comahue. Facultad de Informatica; Argentina
Fil: Montenegro, Ayelén. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; Argentina
Fil: Rodríguez, Andrea. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; Argentina
Fil: Muñoz, Angel. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; Argentina
Materia
reusability
big data systems
variety identification
agrometeorology domain
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/260540
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System DevelopmentsBuccella, AgustinaCechich, AlejandraSaurin, FedericoMontenegro, AyelénRodríguez, AndreaMuñoz, Angelreusabilitybig data systemsvariety identificationagrometeorology domainhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data systems (BDSs) can be approached from different perspectives, all of them useful, depending on the objectives pursued. In particular, in this work, we address BDSs in the area of software engineering, contributing to the generation of novel methodologies and techniques for software reuse. In this article, we propose a methodology to develop reusable BDSs by mirroring activities from software product line engineering. This means that the process of building BDSs is approached by analyzing the variety of domain features and modeling them as a family of related assets. The contextual perspective of the proposal, along with its supporting tool, is introduced through a case study in the agrometeorology domain. The characterization of variables for frost analysis exemplifies the importance of identifying variety, as well as the possibility of reusing previous analyses adjusted to the profile of each case. In addition to showing interesting findings from the case, we also exemplify our concept of context variety, which is a core element in modeling reusable BDSs.Fil: Buccella, Agustina. Universidad Nacional del Comahue. Facultad de Informatica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; ArgentinaFil: Cechich, Alejandra. Universidad Nacional del Comahue. Facultad de Informatica; ArgentinaFil: Saurin, Federico. Universidad Nacional del Comahue. Facultad de Informatica; ArgentinaFil: Montenegro, Ayelén. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; ArgentinaFil: Rodríguez, Andrea. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; ArgentinaFil: Muñoz, Angel. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; ArgentinaMDPI2024-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/260540Buccella, Agustina; Cechich, Alejandra; Saurin, Federico; Montenegro, Ayelén; Rodríguez, Andrea; et al.; A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments; MDPI; Information; 15; 11; 10-2024; 1-292078-2489CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2078-2489/15/11/661info:eu-repo/semantics/altIdentifier/doi/10.3390/info15110661info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:20Zoai:ri.conicet.gov.ar:11336/260540instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:53:21.18CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
title A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
spellingShingle A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
Buccella, Agustina
reusability
big data systems
variety identification
agrometeorology domain
title_short A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
title_full A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
title_fullStr A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
title_full_unstemmed A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
title_sort A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments
dc.creator.none.fl_str_mv Buccella, Agustina
Cechich, Alejandra
Saurin, Federico
Montenegro, Ayelén
Rodríguez, Andrea
Muñoz, Angel
author Buccella, Agustina
author_facet Buccella, Agustina
Cechich, Alejandra
Saurin, Federico
Montenegro, Ayelén
Rodríguez, Andrea
Muñoz, Angel
author_role author
author2 Cechich, Alejandra
Saurin, Federico
Montenegro, Ayelén
Rodríguez, Andrea
Muñoz, Angel
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv reusability
big data systems
variety identification
agrometeorology domain
topic reusability
big data systems
variety identification
agrometeorology domain
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data systems (BDSs) can be approached from different perspectives, all of them useful, depending on the objectives pursued. In particular, in this work, we address BDSs in the area of software engineering, contributing to the generation of novel methodologies and techniques for software reuse. In this article, we propose a methodology to develop reusable BDSs by mirroring activities from software product line engineering. This means that the process of building BDSs is approached by analyzing the variety of domain features and modeling them as a family of related assets. The contextual perspective of the proposal, along with its supporting tool, is introduced through a case study in the agrometeorology domain. The characterization of variables for frost analysis exemplifies the importance of identifying variety, as well as the possibility of reusing previous analyses adjusted to the profile of each case. In addition to showing interesting findings from the case, we also exemplify our concept of context variety, which is a core element in modeling reusable BDSs.
Fil: Buccella, Agustina. Universidad Nacional del Comahue. Facultad de Informatica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina
Fil: Cechich, Alejandra. Universidad Nacional del Comahue. Facultad de Informatica; Argentina
Fil: Saurin, Federico. Universidad Nacional del Comahue. Facultad de Informatica; Argentina
Fil: Montenegro, Ayelén. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; Argentina
Fil: Rodríguez, Andrea. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; Argentina
Fil: Muñoz, Angel. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria Alto Valle; Argentina
description The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data systems (BDSs) can be approached from different perspectives, all of them useful, depending on the objectives pursued. In particular, in this work, we address BDSs in the area of software engineering, contributing to the generation of novel methodologies and techniques for software reuse. In this article, we propose a methodology to develop reusable BDSs by mirroring activities from software product line engineering. This means that the process of building BDSs is approached by analyzing the variety of domain features and modeling them as a family of related assets. The contextual perspective of the proposal, along with its supporting tool, is introduced through a case study in the agrometeorology domain. The characterization of variables for frost analysis exemplifies the importance of identifying variety, as well as the possibility of reusing previous analyses adjusted to the profile of each case. In addition to showing interesting findings from the case, we also exemplify our concept of context variety, which is a core element in modeling reusable BDSs.
publishDate 2024
dc.date.none.fl_str_mv 2024-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/260540
Buccella, Agustina; Cechich, Alejandra; Saurin, Federico; Montenegro, Ayelén; Rodríguez, Andrea; et al.; A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments; MDPI; Information; 15; 11; 10-2024; 1-29
2078-2489
CONICET Digital
CONICET
url http://hdl.handle.net/11336/260540
identifier_str_mv Buccella, Agustina; Cechich, Alejandra; Saurin, Federico; Montenegro, Ayelén; Rodríguez, Andrea; et al.; A Context-Based Perspective on Frost Analysis in Reuse-Oriented Big Data-System Developments; MDPI; Information; 15; 11; 10-2024; 1-29
2078-2489
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2078-2489/15/11/661
info:eu-repo/semantics/altIdentifier/doi/10.3390/info15110661
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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