A context-based perspective on frost analysis in reuse-oriented big data-system developments

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 p...

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Autores principales: Bucella, Agustina, Cechich, Alejandra, Saurin, Federico, Montenegro, Ayelen, Rodriguez, Andrea Betiana, Muñoz, Angel Rafael
Formato: info:ar-repo/semantics/artículo
Lenguaje:Inglés
Publicado: MDPI 2025
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/23266
https://www.mdpi.com/2078-2489/15/11/661
https://doi.org/10.3390/info15110661
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author Bucella, Agustina
Cechich, Alejandra
Saurin, Federico
Montenegro, Ayelen
Rodriguez, Andrea Betiana
Muñoz, Angel Rafael
author_browse Bucella, Agustina
Cechich, Alejandra
Montenegro, Ayelen
Muñoz, Angel Rafael
Rodriguez, Andrea Betiana
Saurin, Federico
author_facet Bucella, Agustina
Cechich, Alejandra
Saurin, Federico
Montenegro, Ayelen
Rodriguez, Andrea Betiana
Muñoz, Angel Rafael
author_sort Bucella, Agustina
collection INTA Digital
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.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
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publishDateRange 2025
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spelling INTA232662025-08-01T10:54:18Z A context-based perspective on frost analysis in reuse-oriented big data-system developments Bucella, Agustina Cechich, Alejandra Saurin, Federico Montenegro, Ayelen Rodriguez, Andrea Betiana Muñoz, Angel Rafael Macrodato Desarrollo de Programas Informáticos Procesamiento de Datos Análisis de Datos Helada Agrometeorología Big Data Software Development Data Processing Data Analysis Frost Agrometeorology Reusabilidad Sistemas de Big Data Identificación de Variedades Dominio de la Agrometeorología Reusability Big Data Systems Variety Identification Agrometeorology Domain 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. EEA Alto Valle Fil: Bucella, Agustina. Universidad Nacional del Comahue. Facultad de Informática. Departamento de Ingeniería de Sistemas. Grupo de Investigación en Ingeniería de Software del Comahue (GIISCo); Argentina Fil: Cechich, Alejandra. Universidad Nacional del Comahue. Facultad de Informática. Departamento de Ingeniería de Sistemas. Grupo de Investigación en Ingeniería de Software del Comahue (GIISCo); Argentina Fil: Saurin, Federico. . Universidad Nacional del Comahue. Facultad de Informática. Departamento de Ingeniería de Sistemas. Grupo de Investigación en Ingeniería de Software del Comahue (GIISCo); Argentina Fil: Montenegro, Ayelen. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Alto Valle; Argentina Fil: Rodríguez, Andrea Betiana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Alto Valle; Argentina Fil: Muñoz, Ángel Rafael. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Alto Valle; Argentina 2025-08-01T10:42:12Z 2025-08-01T10:42:12Z 2024-10-22 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/23266 https://www.mdpi.com/2078-2489/15/11/661 2078-2489 https://doi.org/10.3390/info15110661 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf MDPI Information 15 (11) : 661 (October 2024)
spellingShingle Macrodato
Desarrollo de Programas Informáticos
Procesamiento de Datos
Análisis de Datos
Helada
Agrometeorología
Big Data
Software Development
Data Processing
Data Analysis
Frost
Agrometeorology
Reusabilidad
Sistemas de Big Data
Identificación de Variedades
Dominio de la Agrometeorología
Reusability
Big Data Systems
Variety Identification
Agrometeorology Domain
Bucella, Agustina
Cechich, Alejandra
Saurin, Federico
Montenegro, Ayelen
Rodriguez, Andrea Betiana
Muñoz, Angel Rafael
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
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_short A context-based perspective on frost analysis in reuse-oriented big data-system developments
title_sort context based perspective on frost analysis in reuse oriented big data system developments
topic Macrodato
Desarrollo de Programas Informáticos
Procesamiento de Datos
Análisis de Datos
Helada
Agrometeorología
Big Data
Software Development
Data Processing
Data Analysis
Frost
Agrometeorology
Reusabilidad
Sistemas de Big Data
Identificación de Variedades
Dominio de la Agrometeorología
Reusability
Big Data Systems
Variety Identification
Agrometeorology Domain
url http://hdl.handle.net/20.500.12123/23266
https://www.mdpi.com/2078-2489/15/11/661
https://doi.org/10.3390/info15110661
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