scholarly journals A model for initiating research data management services at academic libraries

2019 ◽  
Vol 107 (3) ◽  
Author(s):  
Kevin B. Read ◽  
Jessica Koos ◽  
Rebekah S. Miller ◽  
Cathryn F. Miller ◽  
Gesina A. Phillips ◽  
...  
Keyword(s):  
Data Management ◽  
Research Data ◽  
Data Series ◽  
Pilot Program ◽  
Data Services ◽  
Research Data Management ◽  
Hands On ◽  
Medical Libraries ◽  
Training Resources ◽  
Educational Modules

Background: Librarians developed a pilot program to provide training, resources, strategies, and support for medical libraries seeking to establish research data management (RDM) services. Participants were required to complete eight educational modules to provide the necessary background in RDM. Each participating institution was then required to use two of the following three elements: (1) a template and strategies for data interviews, (2) a teaching tool kit to teach an introductory RDM class, or (3) strategies for hosting a data class series.Case Presentation: Six libraries participated in the pilot, with between two and eight librarians participating from each institution. Librarians from each institution completed the online training modules. Each institution conducted between six and fifteen data interviews, which helped build connections with researchers, and taught between one and five introductory RDM classes. All classes received very positive evaluations from attendees. Two libraries conducted a data series, with one bringing in instructors from outside the library.Conclusion: The pilot program proved successful in helping participating librarians learn about and engage with their research communities, jump-start their teaching of RDM, and develop institutional partnerships around RDM services. The practical, hands-on approach of this pilot proved to be successful in helping libraries with different environments establish RDM services. The success of this pilot provides a proven path forward for libraries that are developing data services at their own institutions.

scholarly journals A Pilot to Initiate Research Data Management Services Within Academic Libraries Helps Librarians to Learn About, Engage With, and Enhance Skills Within Their Research Communities

2021 ◽  
Vol 16 (1) ◽  
pp. 104-106
Author(s):  
Joanne M. Muehllenbach
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Pilot Project ◽  
Health Sciences ◽  
Research Data ◽  
Data Series ◽  
Pilot Program ◽  
Research Data Management ◽  
Educational Modules ◽  
Management Services

A Review of: Read, K. B, Koos, J., Miller, R. S., Miller, C. F., Phillips, G. A., Scheinfeld, L., & Surkis, A. (2019). A model for initiating research data management services at academic libraries. Journal of the Medical Library Association, 107(3), 432–441. https://doi.org/10.5195/jmla.2019.545 Abstract Objectives – To initiate or expand research data management (RDM) services within the participating libraries serving health sciences populations. Design – Case report. Setting – Six institutions consisting of three academic health sciences and three university libraries within the National Network of Libraries of Medicine Middle Atlantic Region in the United States of America. Subjects – Between two and eight librarians participated from each institution, for a total of twenty-six librarian participants.  Methods – Pre-pilot phone interviews were conducted and included open-ended questions about RDM services, the library’s motivation for participating, and their degree of institutional commitment. To deepen their understanding of RDM, the participants were required to complete eight educational modules that included text, videos, and quizzes. The participating institutions received data interview questions to connect with their research community to be better informed about their attitudes, language, and practices. The participants also received a Teaching Toolkit, complete with slides, a script, and an attendee evaluation form. The participants were provided with a data series, consisting of branded classes for teaching over a designated period with instructors from within and outside of the library. Collaboration with library partners was encouraged as was the use of a focused marketing plan. In fact, a major component of the pilot was the expert support, provided through biweekly meetings that included marketing tips and presentations on such topics as clinical research data management and data visualization.  Finally, post-pilot program interviews were conducted, and the open-ended questions covered the pilot program as a whole and its individual components. Main Results – Of the six participating institutions, five institutions rated the RDM educational modules very positively. Conducting data interviews was valuable for all six institutions because it allowed the librarians to meet with researchers, build relationships, and use what they learned to develop RDM services for the future. The Teaching Toolkit was rated positively by the six institutions, especially for its adaptability, the time saved over developing the content from scratch, and its usability. Finally, the two institutions that held the data series courses stated that the series succeeded in further marketing the RDM services developed by the library.  Conclusion – The pilot project met its objectives: the librarians at the participating institutions completed the educational modules, administered the data interviews, and taught an RDM foundations class based on the Teaching Toolkit. In addition, a data series was hosted at two institutions. The components of the pilot project had the intended results at each institution, and the classes were reviewed favorably. Based on the pilot participants’ positive outcomes, the authors are certain that the freely available program materials would achieve success elsewhere.

Research Data Management Services in Tertiary Institutions in Zimbabwe

2021 ◽  
pp. 419-437
Author(s):  
Josiline Phiri Chigwada
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Policy ◽  
Online Questionnaire ◽  
Tertiary Institutions ◽  
Data Services ◽  
Security Issues ◽  
Research Data Management ◽  
Survey Monkey ◽  
Management Services

The chapter seeks to analyze how librarians in Zimbabwe are responding to increasing librarian roles in the provision of research data services. The study sought to ascertain librarians' awareness and preparedness to offer research data management services at their institutions and determine support required by librarians to effectively deliver research data services. Participants were invited to respond to the survey, and survey monkey was used to administer the online questionnaire. The collected data was analyzed using content analysis, and it was thematically presented. Findings revealed that librarians in Zimbabwe are aware of their role in research data management, but the majority are not prepared to offer research data management services due to a lack of the required skills and resources. Challenges that were noted include lack of research data management policy at institutional levels and information technology issues such as obsolescence and security issues.

scholarly journals Research data services in veterinary medicine libraries

2017 ◽  
Vol 104 (4) ◽  
Author(s):  
Erin E. Kerby, MSI
Keyword(s):  
Veterinary Medicine ◽  
Data Management ◽  
Online Survey ◽  
Research Data ◽  
Management Support ◽  
Job Responsibilities ◽  
Data Services ◽  
Medical Libraries ◽  
Definition Of ◽  
Interest In Research

Objective: The study investigated veterinary medicine librarians’ experience with and perceptions of research data services. Many academic libraries have begun to offer research data services in response to researchers’ increased need for data management support. To date, such services have typically been generic, rather than discipline-specific, to appeal to a wide variety of researchers.Methods: An online survey was deployed to identify trends regarding research data services in veterinary medicine libraries. Participants were identified from a list of contacts from the MLA Veterinary Medical Libraries Section.Results: Although many respondents indicated that they have a professional interest in research data services, the majority of veterinary medicine librarians only rarely or occasionally provide data management support as part of their regular job responsibilities. There was little consensus as to whether research data services should be core to a library’s mission despite their perceived importance to the advancement of veterinary research. Furthermore, most respondents stated that research data services are just as or somewhat less important than the other services that they provide and feel only slightly or somewhat prepared to offer such services.Conclusions: Lacking a standard definition of ‘‘research data’’ and a common understanding of precisely what research data services encompass, it is difficult for veterinary medicine librarians and libraries to define and understand their roles in research data services. Nonetheless, they appear to have an interest in learning more about and providing research data services.

scholarly journals Researcher training in spreadsheet curation

2018 ◽  
Vol 12 (2) ◽  
pp. 116-124
Author(s):  
Gene Lyddon Melzack
Keyword(s):  
Data Management ◽  
Management Training ◽  
Skills Training ◽  
Research Data ◽  
Practical Skills ◽  
Research Data Management ◽  
Qualitative Feedback ◽  
Hands On ◽  
Software Skills ◽  
Data Documentation

Spreadsheets are commonly used across most academic discplines, however their use has been associated with a number of issues that affect the accuracy and integrity of research data. In 2016, new training on spreadsheet curation was introduced at the University of Sydney to address a gap between practical software skills training and generalised research data management training. The approach to spreadsheet curation behind the training was defined and the training's distinction from other spreadsheet curation training offering described.\parThe uptake of and feedback on the training were evaluated. Training attendance was analysed by discipline and by role. Quantitative and qualitative feedback were analysed and discussed. Feedback revealed that many attendees had been expecting and desired practical spreadsheet software skills training. Issues relating to whether or not practical skills training should and can be integrated with curation training were discussed. While attendees were found to be predominantly from science disciplines, qualitative feedback suggests that humanities attendees have specific needs in relation to managing data with spreadsheets that are currently not being met. Feedback also suggested that some attendees would prefer the curation training to be delivered as a longer, more in depth, hands on workshop.\parThe impact of the training was measured using data collected from the University's Research Data Management Planning (RDMP) tool and the Sydney eScholarship Repository. RDMP descriptions of spreadsheet data and records of tabular datasets published in the repository were analysed and assessed for quality and for accompanying data documentation. No significant improvements in data documentation or quality were found, however it is likely too soon after the launch of the training program to have seen much in the way of impact.\parIdentified next steps include clarifying the marketing material promoting to the training to better communicate the curation focus, investigating the needs of humanities researchers working with qualitative data in spreadsheets, and incorporating new material into the training in order to address those needs. Integrating curation training with practical skills training and modifying the training to be more hands on are changes that may be considered in future, but will not be implemented at this stage.

scholarly journals Correction to “A model for initiating research data management services at academic libraries” in 107(3) July, pages 432–41. DOI: http://dx.doi.org/10.5195/jmla.2019.545

2020 ◽  
Vol 108 (2) ◽  
pp. 352
Author(s):  
Katherine G. Akers
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Research Data ◽  
Pilot Program ◽  
Research Data Management ◽  
Management Services

Corrects missing acknowledgments of pilot program participants Deborah Chiarella, Pamela M. Rose, Aletia Morgan, and Gretchen Sneff in “A model for initiating research data management services at academic libraries” in 107(3) July, pages 432–41. DOI: http://dx.doi.org/10.5195/jmla.2019.545.

scholarly journals Potential Roles for Science Librarians in Research Data Management: A Gap Analysis

2021 ◽  
Author(s):  
Wade Bishop ◽  
Hannah Collier ◽  
Ashley Marie Orehek ◽  
Monica Ihli
Keyword(s):  
Data Management ◽  
Gap Analysis ◽  
Research Integrity ◽  
Research Data ◽  
Management Support ◽  
Job Descriptions ◽  
Data Services ◽  
Data Intensive ◽  
Research Data Management ◽  
Role Based

As many sciences move to be more data-intensive, some science librarians are offering more research data services and perform research data management roles. Job analyses provide insight and context to the tasks employees actually do versus what their job descriptions depict or employers assume. Two separate job analyses studies investigated the roles and responsibilities of data services librarians and research integrity officers among the top 10 private and top 10 public higher education institutions. The focus of these interviews was research data management support roles. Comparing these two groups’ responses indicates that the role-based responsibilities for research data services are not always clear within institutions and are predominantly placed on individual researchers or research teams, but science librarians may provide some solutions to address this gap. This paper presents a model for the potential roles of science librarians in research data management.

scholarly journals Why You Need Soft and Non-Technical Skills for Successful Data Librarianship

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Margaret Henderson
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Practical Knowledge ◽  
Soft Skills ◽  
Technical Skills ◽  
Life Cycles ◽  
Research Data ◽  
Relationship Building ◽  
Data Services ◽  
Research Data Management

There are many courses available to teach research data management to librarians and researchers. While these courses can help with technical skills, like programming or statistics, and practical knowledge of data life cycles or data sharing policies, there are “soft skills” and non-technical skills that are needed to successfully start and run data services. While there are many important characteristics of a good data librarian, reference skills, relationship building, collaboration, listening, and facilitation are some of the most important. Giving consideration to these skills will help any data librarian with their multifaceted job.

scholarly journals The Time Has Come… To Talk About Why Research Data Management Isn’t Easy

2020 ◽  
Author(s):  
Carol Tenopir ◽  
Jordan Kaufman ◽  
Robert J. Sandusky ◽  
Danielle Pollock
Keyword(s):  
Data Management ◽  
Academic Libraries ◽  
Research Data ◽  
Data Services ◽  
Research Libraries ◽  
Research Data Management ◽  
The Future

For the last decade, academic libraries have talked with each other and with potential partners about their roles in helping to manage research data and their plans to expand or initiate research data services (RDS). Libraries have the capacity to provide these services, but the range and maturity of research data services from libraries vary considerably. In summer 2019, our team surveyed a sample of academic libraries of all sizes who are members of the Association of College and Research Libraries (ACRL) to find out about their current RDS and plans for the future. This study is a follow-up to surveys of this same group in 2012 and 2015. Our findings include the types of RDS currently being offered in academic libraries, the barriers that hinder RDS implementation, and staff capacity for creating RDS.

scholarly journals Teaching Research Data Management

2014 ◽  
Vol 6 ◽  
Author(s):  
Wendy Mann
Keyword(s):  
Graduate Students ◽  
Data Management ◽  
Management Training ◽  
Boot Camp ◽  
Research Data ◽  
University Libraries ◽  
Management Skills ◽  
Data Services ◽  
Research Data Management ◽  
The University

In January 2014, Mason Libraries along with four other libraries in Virginia used 4-VA telepresence technology to teach a two-day boot camp to graduate students on research data management. Our workshop generated greater than expected interest from graduate students here at Mason. One lesson learned is that there appears to be a gap in the curriculum across all participating schools regarding the teaching of data management skills to budding researchers. This session will be an overview of the learning outcomes from the Data Management Boot Camp, how the University Libraries' Data Services carries out research data management training, and discussion of future plans for helping researchers organize and manage their data.

scholarly journals Practical considerations for a library’s research data management services: the case of the National Institutes of Health Library

2021 ◽  
Vol 109 (3) ◽  
Author(s):  
Soojung Kim ◽  
Sue Yeon Syn
Keyword(s):  
Data Management ◽  
Research Data ◽  
National Institutes Of Health ◽  
User Characteristics ◽  
Data Services ◽  
Research Data Management ◽  
Semistructured Interviews ◽  
Computer Library ◽  
Data Lifecycle

Objective: This study investigates research data management (RDM) services using a crosstab framework with the National Institutes of Health (NIH) Library as a case study to provide practical considerations for libraries seeking to improve their RDM services.Methods: We conducted semistructured interviews with four librarians who provide data services at the NIH Library regarding library user characteristics, RDM services provided, RDM infrastructure, and collaboration experiences. Through the analysis of interview transcripts, we identified and analyzed the NIH Library’s RDM services according to Online Computer Library Center (OCLC)'s three categories of RDM services and the six stages of the data lifecycle.Results: The findings show that the two models’ crosstab framework can provide an overview of an institution’s current RDM services and identify service gaps. The NIH Library tends to take more responsibility in providing education and expertise services while relying more on information technology departments for curation services. The library provides significant support for data creation, analysis, and sharing stages to meet biomedical researchers’ needs, suggesting areas for potential expansion of RDM services in the less supported stages of data description, storage, and preservation. Based on these findings, we recommend three key considerations for libraries: identify gaps in current services, identify services that can be supported via partnerships, and get regular feedback from users.Conclusion: These findings provide a deeper understanding of RDM support on the basis of RDM service categories and the data lifecycle and promote discussion of issues to be considered for future improvements in RDM services.

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