Data-driven scientific research based on public statistics: a bibliometric perspective
dc.contributor.author | Velasco-López, José Eusebio | |
dc.contributor.author | Carrasco González, Ramón Alberto | |
dc.contributor.author | Cobo, Manuel J. | |
dc.contributor.author | Fernández-Avilés, Gema | |
dc.date.accessioned | 2025-01-14T10:18:24Z | |
dc.date.available | 2025-01-14T10:18:24Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Official statistics provide information on different areas of citizens’ lives and are widely used in scientific research as a source of data due to their open data nature and quality assurance. In this context, a bibliometric analysis is carried out using all Scopus publications from 1960 to 2020 that use official statistics as data sources. Thus, 10,777 publications are analyzed using the SciMAT bibliometric analysis software, providing a complete conceptual analysis of the main research topics in the literature through the quantification of the main bibliometric performance indicators, identifying the most important authors, organizations, countries, sources, and intellectual structures corresponding to the main fields of research and bringing classification by subject area as an innovation to the methodology. | |
dc.description.department | Depto. de Estadística y Ciencia de los Datos | |
dc.description.faculty | Fac. de Estudios Estadísticos | |
dc.description.refereed | TRUE | |
dc.description.sponsorship | Spanish State Research Agency | |
dc.description.sponsorship | University of Castilla-La Mancha, Faculty of Law and Social Science | |
dc.description.status | pub | |
dc.identifier.citation | Velasco-López, Jorge-Eusebio; Carrasco, Ramón-Alberto; Cobo, Manuel J.; Fernández-Avilés, Gema (2023). “Data driven scientific research based on public statistics: a bibliometric perspective”. Profesional de la información, v. 32, n. 3, e320314. https://doi.org/10.3145/epi.2023.may.14 | |
dc.identifier.doi | 10.3145/epi.2023.may.14 | |
dc.identifier.officialurl | https://doi.org/10.3145/epi.2023.may.14 | |
dc.identifier.relatedurl | https://revista.profesionaldelainformacion.com/index.php/EPI/article/view/87085 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/114191 | |
dc.issue.number | 3 | |
dc.journal.title | Profesional de la información | |
dc.language.iso | eng | |
dc.publisher | Ediciones Profesionales de la Información | |
dc.relation.projectID | PID2019-105381GA-I00/AEI/10.13039/501100011033 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
dc.rights.accessRights | open access | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.cdu | 024.5:519.23 | |
dc.subject.cdu | 001.8 | |
dc.subject.keyword | Official statistics | |
dc.subject.keyword | Co-word analysis | |
dc.subject.keyword | Strategic diagram | |
dc.subject.keyword | Science mapping analysis | |
dc.subject.keyword | Bibliometric analysis | |
dc.subject.keyword | SciMAT | |
dc.subject.ucm | Estadística aplicada | |
dc.subject.ucm | Bibliometría | |
dc.subject.unesco | 1209 Estadística | |
dc.subject.unesco | 1207.01 Análisis de Actividades | |
dc.title | Data-driven scientific research based on public statistics: a bibliometric perspective | |
dc.type | journal article | |
dc.type.hasVersion | VoR | |
dc.volume.number | 32 | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 658b3e73-df89-4013-b006-45ea9db05e25 | |
relation.isAuthorOfPublication.latestForDiscovery | 658b3e73-df89-4013-b006-45ea9db05e25 |
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