Data-driven scientific research based on public statisticsa bibliometric perspective

  1. Velasco-López, Jorge-Eusebio 1
  2. Carrasco, Ramón-Alberto 1
  3. Cobo, Manuel J. 2
  4. Fernández-Avilés, Gema 3
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

  2. 2 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  3. 3 Universidad de Castilla-La Mancha
    info

    Universidad de Castilla-La Mancha

    Ciudad Real, España

    ROR https://ror.org/05r78ng12

Revista:
El profesional de la información

ISSN: 1386-6710 1699-2407

Año de publicación: 2023

Título del ejemplar: Network activisms

Volumen: 32

Número: 3

Tipo: Artículo

DOI: 10.3145/EPI.2023.MAY.14 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: El profesional de la información

Resumen

Las estadísticas oficiales proporcionan información sobre diferentes ámbitos de la vida de los ciudadanos y se utilizan ampliamente en la investigación científica como fuente de datos, por su naturaleza de datos abiertos y su garantía de calidad. En este contexto, se realiza un análisis bibliométrico utilizando todas las publicaciones de Scopus desde 1960 hasta 2020 que usan las estadísticas oficiales como fuentes de datos. Así, se analizan 10.777 publicaciones mediante el software de análisis bibliométrico SciMAT, obteniendo un análisis conceptual completo de los principales temas de investigación en la bibliografía mediante la cuantificación de los principales indicadores de rendimiento bibliométrico, identificando los autores, organizaciones, países, fuentes y las estructuras intelectuales más importantes correspondientes a los principales campos de investigación y aportando como innovación a la metodología la clasificación por área temática.

Referencias bibliográficas

  • Abraído-Lanza, Ana F.; Dohrenwend, Bruce P.; Ng-Mak, Daisy S.; Turner, J. Blake (1999). “The Latino mortality paradox: a test of the ‘salmon bias’ and healthy migrant hypotheses”. American journal of public health, v. 89, n. 10, pp. 1543-1548. https://doi.org/10.2105/AJPH.89.10.1543
  • Allison, David B.; Fontaine, Kevin R.; Manson, JoAnn E.; Stevens, June; VanItallie, Theodore B. (1999). “Annual deaths attributable to obesity in the United States”. Jama v. 282, n. 16, pp. 1530-1538. https://doi.org/10.1001/jama.282.16.1530
  • Alonso, Sergio; Cabrerizo, Francisco-Javier; Herrera-Viedma, Enrique; Herrera, Francisco (2009). “h-Index: A review focused in its variants, computation and standardization for different scientific fields”. Journal of informetrics, v. 3, n. 4, pp. 273-289. https://doi.org/10.1016/j.joi.2009.04.001
  • Batagelj, Vladimir; Cerinšek, Monika (2013). “On bibliographic networks”. Scientometrics, v. 96, n. 3, pp. 845-864. https://doi.org/10.1007/s11192-012-0940-1
  • Bernstein, Ira M.; Horbar, Jeffrey D.; Badger, Gary J.; Ohlsson, Arne; Golan, Agneta (2000). “Morbidity and mortality among very-low-birth-weight neonates with intrauterine growth restriction”. American journal of obstetrics and gynecology, v. 182, n. 1, pp. 198-206. https://doi.org/10.1016/S0002-9378(00)70513-8
  • Börner, Katy; Chen, Chaomei; Boyack, Kevin W. (2003). “Visualizing knowledge domains”. Annual review of information science and technology, v. 37, n. 1, pp. 179-255. https://doi.org/10.1002/aris.1440370106
  • Buskirk, Trent D.; Kirchner, Antje (2020). “Why machines matter for survey and social science researchers: Exploring applications of machine learning methods for design, data collection, and analysis”. In: Hill, Craig A.; Biemer, Paul P.; Buskirk, Trent D.; Japec, Lilli; Kirchner, Antje; Kolenikov, Stas; Lyberg, Lars E. Big data meets survey science: A collection of innovative methods, pp. 9-62. ISBN: 978 111 897 635 7 https://doi.org/10.1002/9781118976357.ch1
  • Callon, Michel; Courtial, Jean-Pierre; Laville, Francoise (1991). “Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry”. Scientometrics, v. 22, pp. 155-205. https://doi.org/10.1007/BF02019280
  • Callon, Michel; Courtial, Jean-Pierre; Turner, William A.; Bauin, Serge (1983). “From translations to problematic networks: An introduction to co-word analysis”. Social science information, v. 22, n. 2, pp. 191-235. https://doi.org/10.1177/053901883022002003
  • Chen, Jie (2007). “Rapid urbanization in China: A real challenge to soil protection and food security”. Catena, v. 69, n. 1. https://doi.org/10.1016/j.catena.2006.04.019
  • Cobo, Manuel J.; López-Herrera, Antonio G.; Herrera, Francisco; Herrera-Viedma, Enrique (2011a). “A note on the ITS topic evolution in the period 2000-2009 at T-ITS”. IEEE transactions on intelligent transportation systems, v. 13, n. 1, pp. 413-420. https://doi.org/10.1109/TITS.2011.2167968
  • Cobo, Manuel J.; López-Herrera, Antonio G.; Herrera-Viedma, Enrique; Herrera, Francisco (2011b). “Science mapping software tools: Review, analysis, and cooperative study among tools”. Journal of the American Society for Information Science and Technology, v. 62, n. 7, pp. 1382-1402. https://doi.org/10.1002/asi.21525
  • Cobo, Manuel J.; López-Herrera, Antonio G.; Herrera-Viedma, Enrique; Herrera, Francisco (2011c). “An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field”. Journal of informetrics, v. 5, n. 1, pp. 146-166. https://doi.org/10.1016/j.joi.2010.10.002
  • Cobo, Manuel J.; López-Herrera, Antonio G.; Herrera-Viedma, Enrique; Herrera, Francisco (2012). “SciMAT: A new science mapping analysis software tool”. Journal of the American Society for Information Science and Technology, v. 63, n. 8, pp. 1609-1630. https://doi.org/10.1002/asi.22688
  • Coulter, Neal; Monarch, Ira; Konda, Suresh (1998). “Software engineering as seen through its research literature: A study in co-word analysis”. Journal of the American Society for Information Science, v. 49, n. 13, pp. 1206-1223. https://doi.org/10.1002/(SICI)1097-4571(1998)49:13<1206::AID-ASI7>3.0.CO;2-F
  • España (2020). “Real decreto 1110/2020, de 15 de diciembre, por el que se aprueba el Plan Estadístico Nacional 2021-2024”. BOE, n. 340, 30 diciembre . https://www.boe.es/diario_boe/txt.php?id=BOE-A-2020-17283
  • EU (2019). “Directiva (UE) 2019/1024 del Parlamento Europeo y del Consejo relativa a los datos abiertos y la reutilización de la información del sector público (versión refundida)”. Diario oficial de la UE, 26 junio. https://eur-lex.europa.eu/legal-content/ES/TXT/PDF/?uri=CELEX:32019L1024&from=ES
  • EU (2022). “Reglamento (UE) 2022/868 del Parlamento Europeo y del Consejo de 30 de mayo de 2022 relativo a la gobernanza europea de datos y por el que se modifica el Reglamento (UE) 2018/1724 (Reglamento de Gobernanza de Datos)”. Diario oficial de la Unión Europea, n. 152, 3 junio. https://www.boe.es/buscar/doc.php?id=DOUE-L-2022-80835
  • Galán, José-Javier; Carrasco, Ramón-Alberto; LaTorre, Antonio (2022). “Military applications of machine learning: A bibliometric perspective”. Mathematics, v. 10, n. 9, 1397. https://doi.org/10.3390/math10091397
  • García-Villar, Jaume (2012). “La estadística oficial como bien público: retos del presente”. Revista asturiana de economía, n. 46, pp. 61-85. https://dialnet.unirioja.es/servlet/articulo?codigo=4204191
  • Georgiou, Andreas V. (2017). “Towards a global system of monitoring the implementation of UN fundamental principles in national official statistics”. Statistical journal of the IAOS, v. 33. n. 2, pp. 387-397. https://doi.org/10.3233/SJI-160335
  • Gillborn, David (2008). Racism and education: Coincidence or conspiracy?. Routledge. ISBN: 978 0 203928424 https://doi.org/10.4324/9780203928424
  • Giovannini, Enrico; Martins, J. Oliveira; Gamba, Michela (2009). “Statistics, knowledge and governance”. Statistika, v. 6, pp. 471-490.
  • Giri, Chandra; Ochieng, Edward; Tieszen, Larry L.; Zhu, Zq; Singh, Ashbindu; Loveland, Tomas; Masek, Jeff; Duke, Norman (2011). “Status and distribution of mangrove forests of the world using earth observation satellite data”. Global ecology and biogeography, v. 20, n. 1, pp. 154-159. https://doi.org/10.1111/j.1466-8238.2010.00584.x
  • Grantham-McGregor, Sally; Cheung, Yin-Bun; Cueto, Santiago, Glewwe, Paul; Richter, Linda; Strupp, Barbara (2007). “Developmental potential in the first 5 years for children in developing countries”. The lancet, v. 369, n. 9555, pp. 60-70. https://doi.org/10.1016/S0140-6736(07)60032-4
  • Groves, Robert M. (2011). “Three eras of survey research”. Public opinion quarterly, v. 75, n. 5, pp. 861-871. https://doi.org/10.1093/poq/nfr057
  • Gustavsson, Anders; Svensson, Mikael; Jacobi, Frank; Allgulander, Christer; Alonso, Jordi; Beghi, Ettore; Dodel, Richard; Ekman, Mattias; Faravelli, Carlo; Fratiglioni, Laura; Gannon, Brenda; Jones, David H.; Jennum, Poul; Jordanova, Albena; Jönsson, Linus; Karampampa, Korinna; Knapp, Martin; Kolbelt, Gisela; Kurth, Tobias; Lieb, Roselind; Linde, Mattias; Ljungcrantz, Christina; Maercker, Andreas; Melin, Beatrice; Moscarilli, Massimo; Musayev, Amir; Norwood, Fiona; Preisig, Martin; Pugliatti, Maura; Rehm, Juergen; Salvador-Carulla, Luis; Schlehofer, Brigitte; Simon, Roland; Steinhausen, Hans-Christoph; Stovner, Lars J.; Vallat, Jean-Michel; Van-den-Bergh, Peter; Van-Os, Jim; Vos, Pieter; Xu, Weili; Wittchen, Hans-Ulrich; Jönsson, Bengt; Olesen, Jes (2011). “Cost of disorders of the brain in Europe 2010”. European neuropsychopharmacology, v. 21, n. 10, pp. 718-779.
  • Harford, Tim (2014). “Big data: A big mistake?”. Significance, v. 14, n. 5, pp. 14-19. https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1740-9713.2014.00778.x
  • He, Qin (1999). “Knowledge discovery through co-word analysis”. Library trends, v. 48, n. 1, p. 133-159. https://www.ideals.illinois.edu/items/8226
  • Henderson, J. Vernon; Storeygard, Adam; Weil, David N. (2012). “Measuring economic growth from outer space”. American economic review, v. 102, n. 2, pp. 994-1028. https://doi.org/10.1257/aer.102.2.994
  • Hippisley-Cox, Julia; Coupland, Carol; Vinogradova, Yana; Robson, John; Minhas, Rubin; Sheikh, Aziz; Brindle, Peter (2008). “Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2”. British medical journal, v. 336, pp. 1475-1482. https://doi.org/10.1136/bmj.39609.449676.25
  • Hirsch, Jorge E. (2005). “An index to quantify an individual’s scientific research output”. Proceedings of the National Academy of Sciences, v. 102, n. 46, pp. 16569-16572. https://doi.org/10.1073/pnas.0507655102
  • Jacob, Ulrike; Brust, Oliver A. (2019). “Confronting the anomaly: directions in (German) economic research after the crisis”. Science in context, v. 32, n. 4, pp. 449-471. https://doi.org/10.1017/S026988972000006X
  • Liu, Zhu; Guan, Dabo; Wei, Wei; Davis, Steven J; Ciais, Philippe; Bai, Jin; Peng, Shushi; Zhang, Qiang; Hubacek, Klaus; Marland, Gregg; Andres, Robert J.; Crawford-Brown, Douglas; Lin, Jintai; Zhao, Hongyan; Hong, Chaopeng; Boden, Thomas A.; Feng, Kuishuang; Peters, Glen P.; Xi, Fengming; Liu, Junguo; Li, Yuan; Zhao, Yu; Zeng, Ning; He, Kebin (2015). “Reduced carbon emission estimates from fossil fuel combustion and cement production in China”. Nature, v. 524, n. 7565, pp. 335-338. https://doi.org/10.1038/nature14677
  • Llewelyn, Charlotte A.; Hewitt, Patricia E.; Knight, Richard S. G.; Amar, K.; Cousens, S.; Mackenzie, J.; Will, Robert G. (2004). “Possible transmission of variant Creutzfeldt-Jakob disease by blood transfusion”. The lancet, v. 363. n. 9407, pp. 417-421. https://doi.org/10.1016/S0140-6736(04)15486-X
  • Lnenicka, Martin; Luterek, Mariusz; Nikiforova, Anastasija (2022). “Benchmarking open data efforts through indices and rankings: Assessing development and contexts of use”. Telematics and informatics, v. 66, 101745. https://doi.org/10.1016/j.tele.2021.101745
  • Martínez, Miguel-Ángel; Herrera, Manuel; López-Gijón, Javier; Herrera-Viedma, Enrique (2004). “H-Classics: Characterizing the concept of citation classics through”. Scientometrics, v. 98, pp. 1971-1983. https://doi.org/10.1007/s11192-013-1155-9
  • Moreno, Caio; Carrasco, Ramón-Alberto; Herrera-Viedma, Enrique (2019). “Data and artificial intelligence strategy: A conceptual enterprise big data arquitecture to enable market-oriented organizations”. IJIMAI, v. 5, n. 6, pp. 7-14. https://doi.org/10.9781/ijimai.2019.06.003
  • Mukherjee, Debmalya; Lim, Weng-Marc; Kumar, Satish; Donthu, Naveen (2022). “Guidelines for advancing theory and practice through bibliometric research”. Journal of business research, v. 148, pp. 101-115. https://doi.org/10.1016/j.jbusres.2022.04.042
  • Multicentre Aneurysm Screening Study Group (2002). “The Multicentre Aneurysm Screening Study (MASS) into the effect of abdominal aortic aneurysm screening on mortality in men: a randomised controlled trial”. The lancet, v. 360, n. 9345, pp. 1531-1539. https://doi.org/10.1016/S0140-6736(02)11522-4
  • Olesen, Jes; Gustavsson, Anders; Svensson, Mikael; Wittchen, H.-U.; Jönsson, Bengt (2012). “The economic cost of brain disorders in Europe”. European journal of neurology, v. 19, n. 1, pp. 155-162. https://doi.org/10.1111/j.1468-1331.2011.03590.x
  • Peto, Richard; Darby, Sarah; Deo, Harz; Silcocks, Paul; Whitley, Elise; Doll, Richard (2000). “Smoking, smoking cessation, and lung cancer in the UK since 1950: combination of national statistics with two case-control studies”. British medical journal, v. 321, n. 7257, pp. 323-329. https://doi.org/10.1136/bmj.321.7257.323
  • Purkayastha, Amrita; Palmaro, Eleonora; Falk-Krzesinski, Holly J.; Baas, Jeroen (2019). “Comparison of two article-level, field-independent citation metrics: Field-Weighted Citation Impact (FWCI) and Relative Citation Ratio (RCR)”. Journal of informetrics, v. 13, n. 2, pp. 635-642. https://doi.org/10.1016/j.joi.2019.03.012
  • Radermacher, Walter J. (2014). “The European statistics code of practice as a pillar to strengthen public trust and enhance quality in official statistics”. Statistical and Social Inquiry Society of Ireland, v. 43, pp. 27-33. http://www.tara.tcd.ie/handle/2262/72773
  • Rodríguez-Ledesma, Antonio; Cobo, Manuel J.; López-Pujalte, Cristina; Herrera-Viedma, Enrique (2015). “An overview of animal science research 1945-2011 through science mapping analysis”. Journal of animal breeding and genetics, v. 132, n. 6, pp. 475-497. https://doi.org/10.1111/jbg.12124
  • Rodríguez-López, María-Eugenia; Alcántara-Pilar, Juan-Miguel; Del-Barrio-García, Salvador; Muñoz-Leiva, Francisco (2020). “A review of restaurant research in the last two decades: A bibliometric analysis”. International journal of hospitality management, v. 87, 102387. https://doi.org/10.1016/j.ijhm.2019.102387
  • Savage, Mike; Devine, Fiona; Cunningham, Niall; Taylor, Mark; Li, Yaojun; Hjellbrekke, Johs; Le-Roux, Brigitte; Friedman, Sam; Miles, Andrew (2013). “A new model of social class? Findings from the BBC’s great British class survey experiment”. Sociology, v. 47, n. 2, pp. 219-250. https://doi.org/10.1177/0038038513481128
  • Small, Henry (1999). “Visualizing science by citation mapping”. Journal of the American Society for Information Science, v. 50, n. 9, p. 799-813. https://doi.org/10.1002/(SICI)1097-4571(1999)50:9<799::AID-ASI9>3.0.CO;2-G
  • Sternitzke, Christian; Bergmann, Isumo (2009). “Similarity measures for document mapping: a comparative study on the level of an individual scientist”. Scientometrics, v. 78, p. 113-130. https://doi.org/10.1007/s11192-007-1961-z
  • Unal, Belgin; Critchley, Julia-Alison; Capewell, Simon (2004). “Explaining the decline in coronary heart disease mortality in England and Wales between 1981 and 2000”. Circulation, v. 109, n. 9, pp. 1101-1107. https://doi.org/10.1161/01.CIR.0000118498.35499.B2
  • United Nations (2014). “Statistical Commission Decision 45/110 on big data and modernization of statistical systems”. Statistics Division, Decision code: 45/110, chapter: I, section: B. https://unstats.un.org/unsd/statcom/decisions-ref/?code=45/110
  • Unece (2017). Guidance on land-use planning, the siting of hazardous activities and related safety aspects. Geneva, Switzerland: United Nations Economic Commission for Europe. https://unece.org/DAM/env/eia/Publications/2017/1735403E_Final_ENG_web.pdf
  • Unece (2019). Use of satellite image and Earth observation data in official statistics. Geneva, Switzerland: United Nations Economic Commission for Europe. https://unece.org/DAM/stats/documents/ece/ces/2019/ECE_CES_2019_16-1906490E.pdf
  • Unece (2020). Guidelines on the shared environmental information system reporting mechanism. Geneva, Switzerland: United Nations Economic Commission for Europe. https://unece.org/sites/default/files/2020-12/2014795E_WEB.pdf
  • Unece (2021). Measuring and monitoring progress towards the Sustainable Development Goals. Geneva, Switzerland: United Nations Economic Commission for Europe. https://unece.org/sites/default/files/2021-04/2012761_E_web.pdf
  • United Nations (2021). The handbook on management and organization of National Statistical Systems. https://unstats.un.org/capacity-development/handbook/html/topic.htm#t=Handbook%2FCover%2FCover.htm
  • Van-Dijk, Jan; Hacker, Kenneth (2003). “The digital divide as a complex and dynamic phenomenon”. The information society, v. 19, n. 4, pp. 315-326. https://doi.org/10.1080/01972240309487
  • Vikat, Andres; Jones, Christopher (2014). Indicators of gender equality. Unece: Geneva, Switzerland. https://unece.org/sites/default/files/2022-02/ECE_CES_37_WEB.pdf