Librarians as High-Impact Research Data Experts

Authors

  • Md Razib Karno UTM Data Management Center, Jabatan Pendaftar Universiti Teknologi Malaysia, Skudai Johor
  • Mohd Subha Salleh UTM Data Management Center, Jabatan Pendaftar Universiti Teknologi Malaysia, Skudai Johor
  • Rafidah Abd Rahim UTM Data Management Center, Jabatan Pendaftar Universiti Teknologi Malaysia, Skudai Johor

DOI:

https://doi.org/10.24191/jikm.v13i2.9112

Keywords:

Data management, librarianship, information and knowledge management, informational behavior

Abstract

High-impact research data assessment can be performed by librarians because they have more knowledge and understanding of managing scholarly publications and research data compared to staff in other departments and are able to identify the research cycle. The role of librarians in the field of library management is constantly evolving. With the increasing importance of big data, organizations are facing a major challenge in storing, managing, analyzing, and using large data sets. In addition, the establishment of data science programs at institutions has meant that librarians must adapt and integrate growing expertise in management, accessibility, and technology to support data scientists. With their expertise and knowledge in data management, analysis, and preservation, librarians are increasingly seen as potential candidates for the role of chief data officer. The result of this report is an analysis of the need for librarians and the expertise that is a priority in the organization, as measured by variables that are the main key, namely, the 7 main megatrends that have a great impact on the analysis, i.e., the 7 key trends that have the greatest impact on this analysis. The results of this study show that the ability of library managers to manage scholarly research data has been demonstrated through their involvement as intermediary librarians or knowledge management officers (KMOs) in faculty, research groups, research consortia, rating audits, institutional hierarchy secretariats, and other needs at the university, organizational, and international levels. This role has also been shown to contribute to the development of a better scientific community, whether as infrastructure developers, setting new policies, working on data governance, effective data integration, training and promotion, and more.

References

Carlson, J. (2013). Opportunities and Barriers for Librarians in Exploring Data: Observations From the Data Curation Profile Workshops. JESLIB, 2(2).

Corrall, S. (2012). Roles and responsibilities: libraries, librarians, and data In G. Pryor (Ed.), Managing Research Data (pp. 105–134)

Committee, A. R. P. a. R. (2018). 2018 Top Trends in Academic Libraries: A Review of the Trends and Issues Affecting Academic Libraries in Higher Education Campari News, 6 (79), 286.

Corbett, M. J., Deardorff, A., & Kovar-Gough, I. (2014, August 1). Emerging Data Management Roles for Health Librarians in Electronic Medical Records

Eclevia, M. R., Fredeluces, J. C. L. T., ECLEVIA, C. J. L., & Maestro, R. S. (2019). What makes a good data librarian? An analysis of job descriptions and specifications for data librarians. Qualitative and Quantitative Methods in Libraries, 8(3), 273-290

Federer, Lisa (2018. Defining data librarianship: A survey of competencies, skills, and training. Journal of the Medical Library Association. 106.

Hussain, A. (2020). Industrial revolution 4.0: implication to libraries and librarians. Library Hi Tech News, 37(1), 1-5.

Ifijeh, G., & Yusuf, F. (2020). Covid–19 pandemic and the future of Nigeria's university system: The quest for libraries' relevance. The Journal of Academic Librarianship, 46(6),

Karno, Md. Razib (2015) Facilitating resource allocation decision through bibliomining: the case of UTM's library. Masters thesis, Universiti Teknologi Mara, Faculty of Management.

Library of Congress (2003). Understanding marc bibliographic: machine readable cataloguing. 7th ed. Website: http://www.loc.gov/marc/umb/

Mabunda, T. T., & Plessis, T. D. (2022). Employees’ perception of knowledge management in academic libraries in the digital age.

Narendra, A. P. (2016). Big data, data analyst, and improving the competence of librarian. Arabic Alphabet Retrieval System for OPAC Using Digital Tree Method Maisyahtus Su’adaa Irfana, Moch Yasin 1-5 Big Data, Data Analyst, and Improving the Competence of Librarian Albertus Pramukti Narendra 6-11 Challenges and Strategies to Develop a Positive Image of the Library, 6.

Neshcheret, A. M., Sherstobitova, A. A., & Zhuravleva, T. Y.. (2019, January 1). Leading trends in regulation of digital economy: best world’s practices.

Porter, Tanya. (2015). Identifying The Data Scientist Amongst Stem Educators: An Introspective Survey Of Work Skills.

President Barack Obama’s Administration Launches Big Data Initiative .... (n.d). https://www.genengnews.com/insights/president-barack-obamas-administration- launches-big-data-initiative-with-200m/

Semeler, Alexandre & Pinto, Adilson. (2019). The different concepts of research data in the approach to data librarianship. Ciência da Informação. 48. 114-129.

Voss, A. and Procter, R. (2009), "Virtual research environments in scholarly work and communications". Library High Tech. Vol. 27 No. 2, pp. 174-190

Whitmire, A. L., Boock, M., Sutton, S. C. (2015). Variability In Academic Research Data Management Practices. Program: Electronic Library and Information Systems, 4(49), 382-407.

Zhan, Ming & Widen, Gunilla. (2017). Understanding big data in librarianship. Journal of Librarianship and Information Science. 51. 561-576.

Downloads

Published

01-10-2023

How to Cite

Karno, M. R., Salleh, M. S., & Abd Rahim, R. (2023). Librarians as High-Impact Research Data Experts. Journal of Information and Knowledge Management, 13(2), 57–65. https://doi.org/10.24191/jikm.v13i2.9112

Issue

Section

Articles