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Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction

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Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction

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dc.contributor.author Martín-Rodilla, Patricia es_ES
dc.contributor.author Panach Navarrete, Jose Ignacio es_ES
dc.contributor.author González-Pérez, César Augusto es_ES
dc.contributor.author Pastor López, Oscar es_ES
dc.date.accessioned 2019-05-25T20:38:47Z
dc.date.available 2019-05-25T20:38:47Z
dc.date.issued 2018 es_ES
dc.identifier.issn 0169-023X es_ES
dc.identifier.uri http://hdl.handle.net/10251/121075
dc.description.abstract [EN] Any knowledge generation process involves raw data comprehension, evaluation and inferential reasoning. These practices, common to different disciplines, are known as data analysis, and represent the most important set of activities in research contexts. Researchers use data analysis software methods and tools for generating new knowledge in their daily data analysis. In recent years, data analysis software has been incorporating explicit references in modelling of cognitive processes, in order to improve the assistance offered in data analysis tasks. However, data analysis software commercial suites are still resisting this inclusion, and there is little empirical work done in knowing more about how cognitive aspects inclusion in software helps researchers in analyzing data. In this paper, we evaluate the impact produced by the explicit inclusion of cognitive processes in the assistance logic of software tools design and development. We conducted an empirical experiment comparing data analysis performance using traditional software versus data analysis performance using software-assistance tools which incorporate cognitive processes in their design. The experiment is designed in terms of accuracy, efficiency, productivity and user satisfaction during the data analysis made by researchers. It allowed us to find some clear benefits of the cognitive inclusion in the software designed for research contexts, with statistically significant differences in terms of accuracy, productivity and researcher's satisfaction in support of this explicit inclusion, although some efficiency weaknesses are detected. We also discuss the implications of these results for the priority of cognitive inclusion in the software tools design for research contexts data analysis. es_ES
dc.description.sponsorship This paper has the support of Generalitat Valenciana through project IDEO (PROMETEOII/2014/039) and Spanish Ministry of Science and Innovation through project DataME (ref: TIN2016-80811-P). es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation GV/PROMETEOII/2014/039 es_ES
dc.relation AEI/TIN2016-80811-P es_ES
dc.relation.ispartof Data & Knowledge Engineering es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Data-analysis es_ES
dc.subject Software-assistance es_ES
dc.subject Data-analysis measurement es_ES
dc.subject Data-analysis performance es_ES
dc.subject Cognitive processes es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.datak.2018.06.003 es_ES
dc.rights.accessRights Embargado es_ES
dc.date.embargoEndDate 2020-07-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Centro de Investigación en Métodos de Producción de Software - Centre d'Investigació en Mètodes de Producció de Software es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Martín-Rodilla, P.; Panach Navarrete, JI.; González-Pérez, CA.; Pastor López, O. (2018). Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction. Data & Knowledge Engineering. 116:177-204. https://doi.org/10.1016/j.datak.2018.06.003 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1016/j.datak.2018.06.003 es_ES
dc.description.upvformatpinicio 177 es_ES
dc.description.upvformatpfin 204 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 116 es_ES
dc.relation.pasarela 379098 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES


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