Journal:Assessment of and response to data needs of clinical and translational science researchers and beyond

From LIMSWiki
Revision as of 21:26, 11 July 2016 by Shawndouglas (talk | contribs) (Added content. Saving and adding more.)
Jump to navigationJump to search
Full article title Assessment of and response to data needs of clinical and translational science researchers and beyond
Journal Journal of eScience Librarianship
Author(s) Norton, Hannah F.; Tennant, Michele R.; Botero, Cecilia; Garcia-Milian, Rolando
Author affiliation(s) University of Florida, Yale University
Primary contact Email: nortonh at ufl dot edu
Year published 2016
Volume and issue 5 (1)
Page(s) e1090
DOI 10.7191/jeslib.2016.1090
ISSN 2161-3974
Distribution license Creative Commons Attribution 4.0 International
Website http://escholarship.umassmed.edu/jeslib/vol5/iss1/2/
Download http://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1090&context=jeslib (PDF)
This article should not be considered complete until this message box has been removed. This is a work in progress.

Abstract

Objective and setting: As universities and libraries grapple with data management and “big data,” the need for data management solutions across disciplines is particularly relevant in clinical and translational science research, which is designed to traverse disciplinary and institutional boundaries. At the University of Florida Health Science Center Library, a team of librarians undertook an assessment of the research data management needs of clinical and translation science (CTS) researchers, including an online assessment and follow-up one-on-one interviews.

Design and Methods: The 20-question online assessment was distributed to all investigators affiliated with UF’s Clinical and Translational Science Institute (CTSI) and 59 investigators responded. Follow-up in-depth interviews were conducted with nine faculty and staff members.

Results: Results indicate that UF’s CTS researchers have diverse data management needs that are often specific to their discipline or current research project and span the data lifecycle. A common theme in responses was the need for consistent data management training, particularly for graduate students; this led to localized training within the Health Science Center and CTSI, as well as campus-wide training. Another campus-wide outcome was the creation of an action-oriented Data Management/Curation Task Force, led by the libraries and with participation from Research Computing and the Office of Research.

Conclusions: Initiating conversations with affected stakeholders and campus leadership about best practices in data management and implications for institutional policy shows the library’s proactive leadership and furthers our goal to provide concrete guidance to our users in this area.

Keywords: needs assessment, clinical and translational science, service development

Objective and settings

Biomedical researchers work with considerable amounts of heterogeneous data; managing these datasets raises new challenges in terms of acquiring, archiving, annotating, and analyzing data. Libraries across the nation and the world are developing tools to manage this research data, extending natural skills within libraries for organizing, sharing, and archiving information, as well as educating staff about best practices. This stems largely from an increased interest in data management and data sharing at the researcher level, fueled by both funders’ inclusion of data management plan requirements in proposals and by collaborative, large-scale research projects that generate data that is “big” and diverse.[1] The need for data management solutions across disciplines is particularly relevant in clinical and translational science (CTS) research, which is designed to cut across disciplinary and institutional boundaries. Data sharing, organization, storage, and security must scale up to meet these growing needs.

A number of roles in data management and curation have been proposed for librarians including, among others: hosting institutional and disciplinary repositories, developing data publication standards, supporting documentation and metadata use, training researchers and students in funders’ requirements and best practices in data management, working more directly with offices of research, deploying existing tools, hosting data management events (symposia, reflective workshops), embedding into research laboratories to provide data management solutions, and advocating for data sharing.[2][3][4][5][6][7][8][9][10][11][12] Reznick-Zellen et al.[13] postulate three “tiers” of library-based data management services: education (for example, LibGuides, webpages, and workshops), consultation (on data management plans, metadata standards, repository deposition, etc.), and infrastructure (data staging platforms and repositories).

With limited resources available, an integral step to developing these new services is identifying specific needs of the patrons to whom these services are targeted and ensuring that time and resources go into services that truly map to those needs. Needs assessments can also illuminate issues outside of the scope of direct library services, but for which librarians can be advocates on the institutional level. Although the importance of needs assessment is widely agreed upon[14] and a number of libraries have performed such assessments of data management needs[15][16][17][18][19][8][11][20], a 2009 survey of ARL institutions indicated that 62% of responding institutions had not performed a data needs assessment although 73% of libraries had some involvement in e-Science at their institution.[21]

References

  1. ↑ National Science Board (September 2005). "Long-Lived Digital Data Collections Enabling Research and Education in the 21st Century". National Science Foundation. pp. 89. http://www.nsf.gov/pubs/2005/nsb0540/. 
  2. ↑ Gold, A. (2007). "Cyberinfrastructure, Data, and Libraries, Part 2: Libraries and the Data Challenge: Roles and Actions for Libraries". D-Lib Magazine 13. doi:10.1045/july20september-gold-pt2. 
  3. ↑ Charbonneau, D.H. (2013). "Strategies for Data Management Engagement". Medical Reference Services Quarterly 32 (3): 365-74. doi:10.1080/02763869.2013.807089. PMID 23869641. 
  4. ↑ Garritano, J.R.; Carlson, J.R. (2009). "A Subject Librarian's Guide to Collaborating on e-Science Projects". Issues in Science and Technology Librarianship 57 (Spring 2009). doi:10.5062/F42B8VZ3. 
  5. ↑ Heidorn, P.B. (2011). "The Emerging Role of Libraries in Data Curation and E-science". Journal of Library Administration 51 (7–8): 662–672. doi:10.1080/01930826.2011.601269. 
  6. ↑ Rambo, N. (2009). "E-science and biomedical libraries". Journal of the Medical Library Association 97 (3): 159–161. doi:10.3163/1536-5050.97.3.001. PMC PMC2706433. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2706433. 
  7. ↑ Reed, R.B. (2015). "Diving into Data: Planning a Research Data Management Event". Journal of eScience Librarianship 4 (1): e1071. doi:10.7191/jeslib.2015.1071. 
  8. ↑ 8.0 8.1 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. 
  9. ↑ Goldman, J.; Kafel, D.; Martin, E.R. (2015). "Assessment of Data Management Services at New England Region Resource Libraries". Journal of eScience Librarianship 4 (1): e1068. doi:10.7191/jeslib.2015.1068. 
  10. ↑ Piorun, M.E.; Kafel, D.; Leger-Hornby, T. et al. (2012). "Teaching Research Data Management: An Undergraduate/Graduate Curriculum". Journal of eScience Librarianship 1 (1): e1003. doi:10.7191/jeslib.2012.1003. 
  11. ↑ 11.0 11.1 Rambo, Neil (22 October 2015). "Research Data Management Roles for Libraries" (PDF). http://www.sr.ithaka.org/wp-content/uploads/2015/10/SR-Issue_Brief_Research_Data_Management_1022151.pdf. 
  12. ↑ Nelson, M.S. (2015). "Data Management Outreach to Junior Faculty Members: A Case Study". Journal of eScience Librarianship 4 (1): e1076. doi:10.7191/jeslib.2015.1076. 
  13. ↑ Reznik-Zellen, R.C.; Adamick, J.; McGinty, S. (2012). "Tiers of Research Data Support Services". Journal of eScience Librarianship 1 (1): e1002. doi:10.7191/jeslib.2012.1002. 
  14. ↑ Foster, N.F.; Gibbons, S., ed. (2007) (PDF). Studying Students: The Undergraduate Research Project at the University of Rochester. Chicago: Association of College and Research Libraries. pp. 90. ISBN 9780838984376. http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/booksanddigitalresources/digital/Foster-Gibbons_cmpd.pdf. 
  15. ↑ Anderson, N.R.; Lee, S.; Brockenbrough, J.S. et al. (2007). "Issues in Biomedical Research Data Management and Analysis: Needs and Barriers". JAMIA 14 (4): 478–488. doi:10.1197/jamia.M2114. PMC PMC2244904. PMID 17460139. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2244904. 
  16. ↑ Witt, M.; Carlson, J.; Brandt, D.S.; Cragin, M.H. (2009). "Constructing Data Curation Profiles". International Journal of Digital Curation 4 (3): 93–103. doi:10.2218/ijdc.v4i3.117. 
  17. ↑ Bardyn, T.P.; Resnick, T.; Camina, S.K. (2012). "Translational Researchers’ Perceptions of Data Management Practices and Data Curation Needs: Findings from a Focus Group in an Academic Health Sciences Library". Journal of Web Librarianship 6 (4): 274–287. doi:10.1080/19322909.2012.730375. 
  18. ↑ Reich, M.; Shipman, J.P.; Narus, S.P. et al. (2013). "Assessing clinical researchers' information needs to create responsive portals and tools: My Research Assistant (MyRA) at the University of Utah: A case study". Journal of the Medical Library Association 101 (1): 4–11. doi:10.3163/1536-5050.101.1.002. PMC PMC3543136. PMID 23405041. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543136. 
  19. ↑ Guindon, A. (2014). "Research Data Management at Concordia University: A Survey of Current Practices" (PDF). Feliciter 60 (2): 15–17. http://cla.ca/wp-content/uploads/60_2.pdf. 
  20. ↑ Weller, T.; Monroe-Gulick, A. (2015). "Differences in the Data Practices, Challenges, and Future Needs of Graduate Students and Faculty Members". Journal of eScience Librarianship 4 (1): e1070. doi:10.7191/jeslib.2015.1070. 
  21. ↑ Soehner, C.; Steeves, C.; Ward, J. (23 June 2010). "e-Science and data support services: a survey of ARL members". 31st Annual IATUL Conference. Purdue University. http://docs.lib.purdue.edu/iatul2010/conf/day3/1/. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. References were originally listed alphabetically; they were converted to the standard wiki inline format, in order of appearance.

Retrieved from "https://www.limswiki.org/index.php?title=Journal:Assessment_of_and_response_to_data_needs_of_clinical_and_translational_science_researchers_and_beyond&oldid=26453"