Education Needs in Research Data Management for Science-Based Disciplines
Self-Assessment Surveys of Graduate Students and Faculty at Two Public Universities
Research data management is a prominent and evolving consideration for the academic community, especially in scientific disciplines. This research study surveyed 131 graduate students and 79 faculty members in the sciences at two public doctoral universities to determine the importance, knowledge, and interest levels around research data management training and education. The authors adapted 12 competencies for measurement in the study. Graduate students and faculty ranked the following areas most important among the 12 competencies: ethics and attribution, data visualization, and quality assurance. Graduate students indicated they were least knowledgeable and skilled in data curation and re-use, metadata and data description, data conversion and interoperability, and data preservation. Their responses generally matched the perceptions of faculty. The study also examined how graduate students learn research data management, and how faculty perceive that their students learn research data management. Results showed that graduate students utilize self-learning most often and that faculty may be less influential in research data management education than they perceive. Responses for graduate students between the two institutions were not statistically different, except in the area of perceived deficiencies in data visualization competency.
[UNC]. 2018 Spring Final Enrollment Profile [Internet]. Greeley (CO): University of Northern Colorado, Institutional Reporting and Analysis Services; 2018 [cited 2018 Jul 26]. Available from: http://www.unco.edu/institutional-reporting-analysis-services/pdf/enrollment-stats/Spring2018Final.pdf.
Akers, K.G. & Doty, J. 2013. Disciplinary differences in faculty research data management practices and perspectives. International Journal of Digital Curation 8(2):5-26. DOI: 10.2218/ijdc.v8i2.263.
Bracke, M.S. & Fosmire, M. 2015. Teaching data information literacy skills in a library workshop setting: A case study in agricultural and biological engineering. In: Carlson, J. & Johnston, L., editors. Data information literacy: Librarians, data, and the education of a new generation of researchers. West Lafayette (IN): Purdue University Press. p. 129-148. Available at https://www.jstor.org/stable/j.ctt6wq2vh.11.
Carlson, J. & Bracke, M. 2015. Planting the seeds for data literacy: Lessons learned from a student-centered education program. International Journal of Digital Curation 10(1):95-110. DOI: 10.2218/ijdc.v10i1.348.
Carlson, J., Fosmire, M., Miller, C.C. & Nelson, M.S. 2011. Determining data information literacy needs: A study of students and research faculty. portal: Libraries and the Academy 11(2):629-657. DOI: 10.1353/pla.2011.0022.
Carlson, J., Jeffryes, J., Johnston, L.R., Nichols, M., Westra, B. & Wright, S.J. 2015a. An exploration of the data information literacy competencies: Findings from the project interviews. In: Carlson, J. & Johnston, L.R., editors. Data Information Literacy: Librarians, Data, and the Education of a New Generation of Researchers. West Lafayette (IN): Purdue University Press. p. 51-70. Available at https://www.jstor.org/stable/j.ctt6wq2vh.8.
Carlson, J., Johnston, L., Westra, B. & Nichols, M. 2013. Developing an approach for data management education: A report from the Data Information Literacy Project. International Journal of Data Curation 8(1):204-217. DOI: 10.2218/ijdc.v8i1.254.
Carlson, J., Johnston, L.R. & Westra, B. 2015b. Developing the data information literacy project: Approach and methodology. In: Carlson, J. & Johnston, L.R., editors. Data Information Literacy: Librarians, Data, and the Education of a New Generation of Researchers. West Lafayette (IN): Purdue University Press. p. 35-50. http://www.jstor.org/stable/j.ctt6wq2vh.7.
Carlson, J., Nelson, M.S., Johnston, L.R. & Koshoffer, A. 2015c. Developing data literacy programs: Working with faculty, graduate students and undergraduates. Bulletin of the American Society for Information Science and Technology 41(6):14-17. DOI: 10.1002/bult.2015.1720410608.
Carlson, J. & Stowell-Bracke, M. 2013. Data management and sharing from the perspective of graduate students: An examination of the culture and practice at the water quality field station. portal: Libraries and the Academy 13(4):343-361. DOI: 10.1353/pla.2013.0034.
Fernandez, P., Eaker, C., Swauger, S. & Davis, M.L.E.S. 2016. Public progress, data management and the land grant mission: A survey of agriculture researchers’ practices and attitudes at two land-grant institutions. Issues in Science and Technology Librarianship 83. DOI: 10.5062/F49P2ZNN.
Frank, E.P. & Pharo, N. 2016. Academic librarians in data information literacy instruction: A case study in meteorology. College & Research Libraries 77(4):536-552. DOI: 10.5860/crl.77.4.536.
Jahnke, L., Asher, A. & Keralis, S.D.C. 2012. The problem of data [Internet]. Washington (DC): Council on Library and Information Resources [cited 2018 Jul 27]. Report No.: CLIR Publication 154. Available from: https://www.clir.org/pubs/reports/pub154/.
Johnston, L. & Jeffryes, J. 2014. Data management skills needed by structural engineering students: Case study at the University of Minnesota. Journal of Professional Issues in Engineering Education and Practice 140(2):05013002. DOI: 10.1061/(ASCE)EI.1943-5541.0000154.
McLure, M., Level, A.V., Cranston, C.L., Oehlerts, B. & Culbertson, M. 2014. Data curation: A study of researcher practices and needs. portal: Libraries and the Academy 14(2):139-164. DOI: 10.1353/pla.2014.0009.
Mischo, W.H., Wiley, C.A., Schlembach, M.C. & Imker, H.J. 2017. An integrated data management plan instructional program [Internet]. [cited 2018 Jul 27]. 2017 ASEE Annual Conference & Exposition; 2017 Jun 24; Columbus (OH). American Society for Engineering Education. Available from: https://peer.asee.org/27572.
O’Kelly, M., Garrison, J., Merry, B. & Torreano, J. 2015. Building a peer-learning service for students in an academic library. portal: Libraries and the Academy 15(1):163-182. DOI: 10.1353/pla.2015.0000.
Peters, C. & Vaughn, P. 2014. Initiating data management instruction to graduate students at the University of Houston using the New England Collaborative Data Management Curriculum. Journal of eScience Librarianship 3(1):e1064. DOI: 10.7191/jeslib.2014.1064.
Piorun, M., Kafel, D., Leger-Hornby, T., Najafi, S., Martin, E., Colombo, P. & LaPelle, N. 2012. Teaching research data management: An undergraduate/graduate curriculum. Journal of eScience Librarianship 1(1):46-50. DOI: 10.7191/jeslib.2012.1003.
Pouchard, L. & Bracke, M.S. 2016. An analysis of selected data practices: A case study of the Purdue College of Agriculture. Issues in Science and Technology Librarianship 85. DOI: 10.5062/F4057CX4.
Schmidt, L. & Holles, J.H. 2018. Teaching research data management: It takes a team to do it right! [Internet]. [cited 2018 Jul 16]. 2018 ASEE Annual Conference & Exposition; 2018 Jun 23; Salt Lake City (UT). American Society for Engineering Education. Available from: https://peer.asee.org/31061.
[NSF]. Science and engineering degrees: 1966-2010, Appendix B: Classification of fields of study [Internet]. Arlington (VA): National Science Foundation, National Center for Science and Engineering Statistics (US); 2013 [cited 2018 Sep 17]. Available from: https://www.nsf.gov/statistics/nsf13327/content.cfm?pub_id=4266&id=4.
Sheehan, J., Kenning, A., Mannheimer, S., Knobel, C. & Llovet, P. 2015. Data-intensive science and campus IT [Internet]. EDUCAUSE Review [2015 Sep 28; cited 2019 Apr 18]. Available from: https://er.educause.edu/articles/2015/9/data-intensive-science-and-campus-it.
Tenopir, C., Birch, B. & Allard, S. 2012. Academic libraries and research data services: Current practices and plans for the future [Internet]. Chicago (IL): Association of College and Research Libraries. p. 1-54 [cited 2018 Jul 27]. Available from: http://www.ala.org/acrl/issues/whitepapers.
Tenopir, C., Dalton, E.D., Allard, S., Frame, M., Pjesivac, I., Birch, B., Pollock, D. & Dorsett, K. 2015. Changes in data sharing and data reuse practices and perceptions among scientists worldwide. PLoS ONE 10(8):e0134826. DOI: 10.1371/journal.pone.0134826.
Thielen, J., Samuel, S.M., Carlson, J. & Moldwin, M. 2017. Developing and teaching a two-credit data management course for graduate students in climate and space sciences. Issues in Science and Technology Librarianship 86. DOI: 10.5062/F42Z13HQ.
[UW]. University of Wyoming Enrollment Summary Spring 2018 [Internet]. Laramie (WY): University of Wyoming Office of Institutional Analysis; 2018 [cited 2018 Jul 27]. Available from: http://www.uwyo.edu/oia/student/eos/enroll-sum/.
Weller, T. & Monroe-Gulick, A. 2014. Understanding methodological and disciplinary differences in the data practices of academic researchers. Library Hi Tech 32(3):467-482. DOI: 10.1108/LHT-02-2014-0021.
Whitmire, A.L., Boock, M. & Sutton, S.C. 2015. Variability in academic research data management practices: Implications for data services development from a faculty survey. Program 49(4):382-407. DOI: 10.1108/PROG-02-2015-0017.
Wiley, C. & Mischo, W.H. 2016. Data management practices and perspectives of atmospheric scientists and engineering faculty. Issues in Science and Technology Librarianship 85. DOI: 10.5062/F43X84NJ.
Wiley, C.A. & Kerby, E.E. 2018. Managing research data: Graduate student and postdoctoral researcher perspectives. Issues in Science and Technology Librarianship 89. DOI: 10.5062/F4FN14FJ
Copyright (c) 2019 Judith E Pasek, Jennifer Mayer
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.