Los datos pueden ser más importantes que las publicaciones: hay que hacerlos valer
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Resumen
Los datos en una investigación son considerados como las materias primas para la extracción de información o conocimiento científico que sustenta las publicaciones y la toma de medidas. Existe la creencia de que cuando la investigación termina y se publica, los datos utilizados pierden su valor y tienden a desecharse o almacenarse, invisibles e inaccesibles para otros investigadores. Esta es una visión superficial que esconde la realidad de que los datos son uno de los productos primarios más valiosos de la ciencia, con múltiples valores adicionales que permiten afirmar que pueden llegar a ser más importantes incluso que las propias publicaciones. Pero para que se pueda expresar este valor, debe seguirse una serie de aspectos metodológicos que incluyen desde la estructuración apropiada de las matrices o ficheros, su documentación a través de metadatos, la selección y asignación de las licencias, el identificador digital o su publicación como Artículo de datos. En la presente revisión se discuten algunas de estas prácticas para revalorizar los datos de las investigaciones ecológicas y poder explotarlos en toda su extensión, dado el desconocimiento generalizado de la infraestructura existente y los métodos para hacerlos disponibles, recuperables y utilizables por tiempo indefinido. Para ello se responden las preguntas básicas: ¿por qué y para qué? ¿cómo? ¿dónde? y ¿cuándo? Se termina haciendo un llamado al cambio desde la visión tradicional que se enfoca solo en el análisis de los datos. Se requiere una nueva visión que ponga más énfasis en la organización de los datos y su documentación para hacerlos públicos, conjuntamente con los artículos.
Detalles del artículo
Cómo citar
ÁvilaD. D. (2020). Los datos pueden ser más importantes que las publicaciones: hay que hacerlos valer. Acta Botánica Cubana, 219(2). Recuperado a partir de http://revistas.geotech.cu/index.php/abc/article/view/324
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Alonso B, Valladares F. 2006. Bases de datos y metadatos en ecología: compartir para investigar en cambio global. Ecosistemas. 15(2): 83¬88.
Baker M. 2016. Is there a reproducibility crisis? Nature. 533:452-454.
Blischak JD, Davenport ER, Wilson G. 2016. A quick introduction to version control with Git and GitHub. PLOS Computational Biology. 12: e1004668.
Blumenthal D, Campbell E, Anderson M, Causino N, Louis K. 1997. Withholding research results in academic life science. Evidence from a national survey of faculty. Journal of the American Medical Association. 277: 1224-1228.
Boettiger C. 2019. Ecological metadata as linked data. Journal of Open Source Software. 4: 1276.
Boettiger C, Jones MB, Maier M, Mecum B, Salmon M, Clark J. 2019. EML: Read and Write Ecological Metadata Language Files. Disponible en https://cloud.r-project.org/web/packages/EML/index.html (consultado: 01 de septiembre de 2020).
Caldera-Serrano J. 2018. Repositorios públicos frente a la mercantilización de la ciencia: apostando por la ciencia abierta y la evaluación cualitativa. Métodos de Información. 9: 74-101.
Chavan V, Penev L. 2011. The data paper: a mechanism to incentivize data publishing in biodiversity science. BMC Bioinformatics. 12 Suppl 15: S2.
Claerbout J, Karrenbach M. 1992. Electronic documents give reproducible research a new meaning. En: Proceedings of the 62nd annual international meeting of the society of exploration geophysics, New Orleans (Octubre 1992).
Costello MJ, Michener WK, Gahegan M, Zhang Z-Q, Bourne PE. 2013. Biodiversity data should be published, cited, and peer reviewed. Trends in Ecology and Evolution. 28: 454-461.
Couture JL, Blake RE, McDonald G, Ward CL. 2018. A funder-im¬posed data publication requirement seldom inspired data sharing. PLOS ONE. 13: e0199789.
Crowther M, Lim W, y Crowther MA. 2010. Systematic review and meta-analysis methodology. Blood, The Journal of the American Society of Hematology. 116: 3140-3146.
Culina A., Baglioni M., Crowther TW, Visser ME, Woutersen-Windhouwer S, Manghi P 2018. Navigating the unfolding open data land¬scape in ecology and evolution. Nature Ecology and Evolution. 2: 420-426.
Díaz-Delgado R. 2016. La investigación y seguimiento ecológico a largo plazo (LTER). Ecosistemas. 25: 1-3.
Editorial Nature. 2018. Data sharing and the future of sci¬ence. Nature Communications. 9: 2817.
Fegraus EH, Andelman S, Jones MB, Schildhauer M. 2005. Maximiz¬ing the value of ecological data with structured metadata: An introduc¬tion to ecological metadata language (EML) and principles for metadata creation. The Bulletin of the Ecological Society of America. 86: 158-168.
Fiedler K y Schwarz N. 2016. Questionable research practices revisited. Social Psychological and Personality Science 7: 45-52.
Fraser LH. 2020. TRY-A plant trait database of databases. Global Change Biology. 26:189-190.
Fraser, H., T. Parker, S. Nakagawa, A. Barnett y F. Fidler. 2018. Questionable research practices in ecology and evolution. PLOS ONE. https://doi.org/10.1371/journal.pone.0200303
Goodman A, Pepe A, Blocker AW, Borgman CL, Cranmer K, Crosas M, Di Stefano R, Gil Y, Groth P, Hedstrom M, Hogg DW, Kashyap V, Mahabal A, Siemiginowska A, Slavkovic A. 2014. Ten simple rules for the care and feeding of scientific data. PLOS Computational Biology. 10: 1-5.
Hampton SE, Anderson SS, Bagby SC, Gries C, Han X, Hart EM, Jones MB, Lenhardt WC, Macdonald A, Michener WK, Mudge J, Pourmokhtarian A, Schildhauer MP, Woo KH, Zimmerman N. 2015. The Tao of open science for ecology. Ecosphere. 6: art120.
Hart E, Barmby P, LeBauer D, Michonneau F, Mount S, Mulrooney P, Poisot T, Woo KH, Zimmerman NB, Hollister JW. 2016. Ten simple rules for digital data storage. Peer J preprints. 4: e1448v2.
Kervin K, Michener W, Cook R. 2013. Common errors in ecological data sharing. Journal of Science Librarianship. 2: e1024.
Kornfeld DS, Titus SL. 2016. Stop ignoring misconduct. Nature. 537: 29
Kuebbing SE, Reimer AP, Rosenthal SA, Feinberg G, Leiserowitz A, Lau JA, Bradford MA. 2018. Long-term research in ecology and evolution: A survey of challenges and opportunities. Ecological Mono¬graphs. 88: 245-258.
Martone M. (ed.) 2014. Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. San Diego CA: FORCE11. (https://www.force11.org/group/joint-declaration-data-citation-principles-final).
McNutt M. 2014. Reproducibility. Science 343, 229.
Michener WK. 2015a. Ecological data sharing. Ecological Informatics. 29: 33-44.
Michener WK. 2015b. Ten simple rules for creating a good data management plan. PLoS Computational Biology 11(10): e1004525. doi:10.1371/journal. pcbi.1004525.
Michener WK, Brunt JW, Helly JJ, Kirchner TB, Stafford SG. 1997. Nongeospatial metadata for the ecological sciences. Ecological Applications. 7: 330-342.
Michener WK, Jones MB. 2012. Ecoinformatics: supporting ecology as a data-intensive science. Trends in Ecology & Evolution. 27: 85-93.
Munafo MR, Smith GD. 2018. Repeating experiments is not enough. Nature. 553: 399
Nosek BA, Ebersole CR, DeHaven AC, Mellor DT. 2018. The preregistration revolution. Proceedings of the National Academy of Sciences. 115: 2600-2606.
Peng RD. 2011. Reproducible Research in Computational Science. Science. 334: 1226-1227.
Pierce HH, Dev A, Statham E, Bierer BE. 2019. Credit data generators for ddta reuse. Nature. 570: 30-32.
Pigliucci M, Boudry M. 2013. Philosophy of pseudoscience: reconsidering the demarcation problem. University of Chicago Press, Chicago.
Piwowar HA, Day RS, Fridsma DB. 2007. Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE. 2: e308.
Piwowar HA. 2011. Who shares? Who doesn’t? Factors associated with openly archiving raw research data. PLoS ONE. 6(7): e18657.
Reichman OJ, Jones MB, Schildhauer MP. 2011. Challenges and op¬portunities of open data in ecology. Science. 331: 703-705.
Roche DG, Kruuk LEB, Lanfear R, Binning SA. 2015. Public data archiving in ecology and evolution: How well are we doing? PLOS Biology.13: e1002295.
Rodríguez-Sánchez F, Pérez-Luque AJ, Bartomeus I, Varela S. 2016. Ciencia reproducible: qué, por qué, cómo? Ecosistemas. 25: 83-92.
Rüegg J, Gries C, Bond-Lamberty B, Bowen GJ, Felzer BS, McIntyre NE, Soranno PA, Vanderbilt KL, Weathers KC. 2014. Completing the data life cycle: using information management in macrosystems ecology research. Frontiers in Ecology and the Environment. 12: 24-30.
Santos C, Blake J, States DJ. 2005. Supplementary data need to be kept in public repositories. Nature. 438: 738.
Schnitzer SA, Carson WP. 2016. Would Ecology Fail the repeatability test? Bioscience. 66: 98-99.
Sholler D, Ram K, Boettiger C, Katz DS. 2019. Enforcing public data archiving policies in academic publishing: A study of ecology journals. Big Data and Society. 6: 1-18.
Smith C. 2019. EMLassemblyline: A workflow for creating EML. Disponible en https://github.com/EDIorg/EMLassemblyline/blob/mas-ter/DESCRIPTION (consultado: 01 de septiembre de 2020).
Soranno PA. 2019. Six simple steps to share your data when publishing research articles. Limnology and Oceanography Bulletin. 28: 41-44.
Specht A, Bolton MP, Kingsford B, Specht RL, Belbin L. 2018. A story of data won, data lost and data re-found: the realities of ecological data preservation. Biodiversity Data Journal. 6: e28073.
Stodden V, Guo P, Ma Z. 2013. Toward reproducible computational re¬search: An empirical analysis of data and code policy adoption by jour¬nals. PLOS ONE. 8: 1-8.
Strasser C. 2014. The 10 things every new grad student should do. Blog en UC3 - University of California Curation Center. Disponible en https://uc3.cdlib.org/2014/10/14/the-10-things-every-new-grad-student-should-do/ (consultado: 02 de junio de 2020).
Torres-Salinas D, Robinson-García N, Cabezas-Clavijo Á. 2012. Com¬partir los datos de investigación en ciencia: introducción al data sharing. El Profesional de la Información. 21: 173-184.
Vanderbilt KL, Lin C-C, Lu S-S, Kassim AR, He H, Guo X, San Gil I, Blankman D, Porter JH. 2015. Fostering ecological data sharing: collaborations in the International Long Term Ecological Research Network. Ecosphere. 6(10):204. DOI.org/10.1890/ES14-00281.1
Vandewalle P. 2012. Code sharing is associated with research impact in image processing. Computing in Science and Engineering.14: 42-47.
Vines TH, Albert AY, Andrew RL, Débarre F, Bock DG, Franklin MT, Gilbert KJ, Moore JS, Renaut S, Rennison DJ. 2014. The Availability of Research Data Declines Rapidly with Article Age. Current Biology. 24: 94-97.
White E, Baldridge E, Brym Z, Locey K, McGlinn D, Supp S. 2013. Nine simple ways to make it easier to (re)use your data. Ideas in Ecology and Evolution. 6: 1-10.
Whitlock MC. 2011. Data archiving in ecology and evolution: best practices. Trends in Ecology & Evolution. 26: 61 -65.
Wickham H. 2014. Tidy data. Journal of Statistical Software. 59: 1-23
Wieczorek J, Bloom D, Guralnick R, Blum S, Döring M, Giovanni R, Robertson T, Vieglais D. 2012. Darwin core: An evolving community- developed biodiversity data standard. PLoS ONE. 7: e29715.
Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJG, Groth P, Goble C, Grethe JS, Heringa J, Hoen PAC, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, Van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, Van Der Lei J, Van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. 2016. The FAIR guiding principles for sci¬entific data management and stewardship. Scientific Data. 3: 1-9.
Baker M. 2016. Is there a reproducibility crisis? Nature. 533:452-454.
Blischak JD, Davenport ER, Wilson G. 2016. A quick introduction to version control with Git and GitHub. PLOS Computational Biology. 12: e1004668.
Blumenthal D, Campbell E, Anderson M, Causino N, Louis K. 1997. Withholding research results in academic life science. Evidence from a national survey of faculty. Journal of the American Medical Association. 277: 1224-1228.
Boettiger C. 2019. Ecological metadata as linked data. Journal of Open Source Software. 4: 1276.
Boettiger C, Jones MB, Maier M, Mecum B, Salmon M, Clark J. 2019. EML: Read and Write Ecological Metadata Language Files. Disponible en https://cloud.r-project.org/web/packages/EML/index.html (consultado: 01 de septiembre de 2020).
Caldera-Serrano J. 2018. Repositorios públicos frente a la mercantilización de la ciencia: apostando por la ciencia abierta y la evaluación cualitativa. Métodos de Información. 9: 74-101.
Chavan V, Penev L. 2011. The data paper: a mechanism to incentivize data publishing in biodiversity science. BMC Bioinformatics. 12 Suppl 15: S2.
Claerbout J, Karrenbach M. 1992. Electronic documents give reproducible research a new meaning. En: Proceedings of the 62nd annual international meeting of the society of exploration geophysics, New Orleans (Octubre 1992).
Costello MJ, Michener WK, Gahegan M, Zhang Z-Q, Bourne PE. 2013. Biodiversity data should be published, cited, and peer reviewed. Trends in Ecology and Evolution. 28: 454-461.
Couture JL, Blake RE, McDonald G, Ward CL. 2018. A funder-im¬posed data publication requirement seldom inspired data sharing. PLOS ONE. 13: e0199789.
Crowther M, Lim W, y Crowther MA. 2010. Systematic review and meta-analysis methodology. Blood, The Journal of the American Society of Hematology. 116: 3140-3146.
Culina A., Baglioni M., Crowther TW, Visser ME, Woutersen-Windhouwer S, Manghi P 2018. Navigating the unfolding open data land¬scape in ecology and evolution. Nature Ecology and Evolution. 2: 420-426.
Díaz-Delgado R. 2016. La investigación y seguimiento ecológico a largo plazo (LTER). Ecosistemas. 25: 1-3.
Editorial Nature. 2018. Data sharing and the future of sci¬ence. Nature Communications. 9: 2817.
Fegraus EH, Andelman S, Jones MB, Schildhauer M. 2005. Maximiz¬ing the value of ecological data with structured metadata: An introduc¬tion to ecological metadata language (EML) and principles for metadata creation. The Bulletin of the Ecological Society of America. 86: 158-168.
Fiedler K y Schwarz N. 2016. Questionable research practices revisited. Social Psychological and Personality Science 7: 45-52.
Fraser LH. 2020. TRY-A plant trait database of databases. Global Change Biology. 26:189-190.
Fraser, H., T. Parker, S. Nakagawa, A. Barnett y F. Fidler. 2018. Questionable research practices in ecology and evolution. PLOS ONE. https://doi.org/10.1371/journal.pone.0200303
Goodman A, Pepe A, Blocker AW, Borgman CL, Cranmer K, Crosas M, Di Stefano R, Gil Y, Groth P, Hedstrom M, Hogg DW, Kashyap V, Mahabal A, Siemiginowska A, Slavkovic A. 2014. Ten simple rules for the care and feeding of scientific data. PLOS Computational Biology. 10: 1-5.
Hampton SE, Anderson SS, Bagby SC, Gries C, Han X, Hart EM, Jones MB, Lenhardt WC, Macdonald A, Michener WK, Mudge J, Pourmokhtarian A, Schildhauer MP, Woo KH, Zimmerman N. 2015. The Tao of open science for ecology. Ecosphere. 6: art120.
Hart E, Barmby P, LeBauer D, Michonneau F, Mount S, Mulrooney P, Poisot T, Woo KH, Zimmerman NB, Hollister JW. 2016. Ten simple rules for digital data storage. Peer J preprints. 4: e1448v2.
Kervin K, Michener W, Cook R. 2013. Common errors in ecological data sharing. Journal of Science Librarianship. 2: e1024.
Kornfeld DS, Titus SL. 2016. Stop ignoring misconduct. Nature. 537: 29
Kuebbing SE, Reimer AP, Rosenthal SA, Feinberg G, Leiserowitz A, Lau JA, Bradford MA. 2018. Long-term research in ecology and evolution: A survey of challenges and opportunities. Ecological Mono¬graphs. 88: 245-258.
Martone M. (ed.) 2014. Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. San Diego CA: FORCE11. (https://www.force11.org/group/joint-declaration-data-citation-principles-final).
McNutt M. 2014. Reproducibility. Science 343, 229.
Michener WK. 2015a. Ecological data sharing. Ecological Informatics. 29: 33-44.
Michener WK. 2015b. Ten simple rules for creating a good data management plan. PLoS Computational Biology 11(10): e1004525. doi:10.1371/journal. pcbi.1004525.
Michener WK, Brunt JW, Helly JJ, Kirchner TB, Stafford SG. 1997. Nongeospatial metadata for the ecological sciences. Ecological Applications. 7: 330-342.
Michener WK, Jones MB. 2012. Ecoinformatics: supporting ecology as a data-intensive science. Trends in Ecology & Evolution. 27: 85-93.
Munafo MR, Smith GD. 2018. Repeating experiments is not enough. Nature. 553: 399
Nosek BA, Ebersole CR, DeHaven AC, Mellor DT. 2018. The preregistration revolution. Proceedings of the National Academy of Sciences. 115: 2600-2606.
Peng RD. 2011. Reproducible Research in Computational Science. Science. 334: 1226-1227.
Pierce HH, Dev A, Statham E, Bierer BE. 2019. Credit data generators for ddta reuse. Nature. 570: 30-32.
Pigliucci M, Boudry M. 2013. Philosophy of pseudoscience: reconsidering the demarcation problem. University of Chicago Press, Chicago.
Piwowar HA, Day RS, Fridsma DB. 2007. Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE. 2: e308.
Piwowar HA. 2011. Who shares? Who doesn’t? Factors associated with openly archiving raw research data. PLoS ONE. 6(7): e18657.
Reichman OJ, Jones MB, Schildhauer MP. 2011. Challenges and op¬portunities of open data in ecology. Science. 331: 703-705.
Roche DG, Kruuk LEB, Lanfear R, Binning SA. 2015. Public data archiving in ecology and evolution: How well are we doing? PLOS Biology.13: e1002295.
Rodríguez-Sánchez F, Pérez-Luque AJ, Bartomeus I, Varela S. 2016. Ciencia reproducible: qué, por qué, cómo? Ecosistemas. 25: 83-92.
Rüegg J, Gries C, Bond-Lamberty B, Bowen GJ, Felzer BS, McIntyre NE, Soranno PA, Vanderbilt KL, Weathers KC. 2014. Completing the data life cycle: using information management in macrosystems ecology research. Frontiers in Ecology and the Environment. 12: 24-30.
Santos C, Blake J, States DJ. 2005. Supplementary data need to be kept in public repositories. Nature. 438: 738.
Schnitzer SA, Carson WP. 2016. Would Ecology Fail the repeatability test? Bioscience. 66: 98-99.
Sholler D, Ram K, Boettiger C, Katz DS. 2019. Enforcing public data archiving policies in academic publishing: A study of ecology journals. Big Data and Society. 6: 1-18.
Smith C. 2019. EMLassemblyline: A workflow for creating EML. Disponible en https://github.com/EDIorg/EMLassemblyline/blob/mas-ter/DESCRIPTION (consultado: 01 de septiembre de 2020).
Soranno PA. 2019. Six simple steps to share your data when publishing research articles. Limnology and Oceanography Bulletin. 28: 41-44.
Specht A, Bolton MP, Kingsford B, Specht RL, Belbin L. 2018. A story of data won, data lost and data re-found: the realities of ecological data preservation. Biodiversity Data Journal. 6: e28073.
Stodden V, Guo P, Ma Z. 2013. Toward reproducible computational re¬search: An empirical analysis of data and code policy adoption by jour¬nals. PLOS ONE. 8: 1-8.
Strasser C. 2014. The 10 things every new grad student should do. Blog en UC3 - University of California Curation Center. Disponible en https://uc3.cdlib.org/2014/10/14/the-10-things-every-new-grad-student-should-do/ (consultado: 02 de junio de 2020).
Torres-Salinas D, Robinson-García N, Cabezas-Clavijo Á. 2012. Com¬partir los datos de investigación en ciencia: introducción al data sharing. El Profesional de la Información. 21: 173-184.
Vanderbilt KL, Lin C-C, Lu S-S, Kassim AR, He H, Guo X, San Gil I, Blankman D, Porter JH. 2015. Fostering ecological data sharing: collaborations in the International Long Term Ecological Research Network. Ecosphere. 6(10):204. DOI.org/10.1890/ES14-00281.1
Vandewalle P. 2012. Code sharing is associated with research impact in image processing. Computing in Science and Engineering.14: 42-47.
Vines TH, Albert AY, Andrew RL, Débarre F, Bock DG, Franklin MT, Gilbert KJ, Moore JS, Renaut S, Rennison DJ. 2014. The Availability of Research Data Declines Rapidly with Article Age. Current Biology. 24: 94-97.
White E, Baldridge E, Brym Z, Locey K, McGlinn D, Supp S. 2013. Nine simple ways to make it easier to (re)use your data. Ideas in Ecology and Evolution. 6: 1-10.
Whitlock MC. 2011. Data archiving in ecology and evolution: best practices. Trends in Ecology & Evolution. 26: 61 -65.
Wickham H. 2014. Tidy data. Journal of Statistical Software. 59: 1-23
Wieczorek J, Bloom D, Guralnick R, Blum S, Döring M, Giovanni R, Robertson T, Vieglais D. 2012. Darwin core: An evolving community- developed biodiversity data standard. PLoS ONE. 7: e29715.
Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJG, Groth P, Goble C, Grethe JS, Heringa J, Hoen PAC, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, Van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, Van Der Lei J, Van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. 2016. The FAIR guiding principles for sci¬entific data management and stewardship. Scientific Data. 3: 1-9.