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 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 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 From Project to Strategic Vision: Taking the Lead in Research Data Management Support at the University of Sydney Library

2014 ◽  
Vol 9 (1) ◽  
pp. 253-262 ◽  
Author(s):  
Belinda Norman ◽  
Kate Valentine Stanton
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Support ◽  
Policy And Practice ◽  
Roles And Responsibilities ◽  
Strategic Vision ◽  
Research Data Management ◽  
The Commons ◽  
The University ◽  
Project Partner

This paper explores three stories, each occurring a year apart, illustrating an evolution toward a strategic vision for Library leadership in supporting research data management at the University of Sydney. The three stories describe activities undertaken throughout the Seeding the Commons project and beyond, as the establishment of ongoing roles and responsibilities transition the Library from project partner to strategic leader in the delivery of research data management support. Each story exposes key ingredients that characterise research data management support: researcher engagement; partnerships; and the complementary roles of policy and practice.

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 at ETH-Bibliothek

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 284-291 ◽  
Author(s):  
Ana Sesartic ◽  
Matthias Töwe
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Service Providers ◽  
Scientific Practice ◽  
Research Data ◽  
Data Services ◽  
Mutual Learning ◽  
Data Life Cycle ◽  
Long Term Preservation

The management of research data throughout its life-cycle is both a key prerequisite for effective data sharing and efficient long-term preservation of data. This article summarizes the data services and the overall approach to data management as currently practised at ETH-Bibliothek, the main library of ETH Zürich, the largest technical university in Switzerland. The services offered by service providers within ETH Zürich cover the entirety of the data life-cycle. The library provides support regarding conceptual questions, offers training and services concerning data publication and long-term preservation. As research data management continues to play a steadily more prominent part in both the requirements of researchers and funders as well as curricula and good scientific practice, ETH-Bibliothek is establishing close collaborations with researchers, in order to promote a mutual learning process and tackle new challenges.

scholarly journals Modelling the Research Data Lifecycle

2018 ◽  
Vol 12 (2) ◽  
pp. 331-361 ◽  
Author(s):  
Stacy T Kowalczyk
Keyword(s):  
Data Management ◽  
Analytical Techniques ◽  
Research Process ◽  
Initial Study ◽  
Research Data ◽  
Management Support ◽  
File Formats ◽  
Metadata File ◽  
Data Lifecycle ◽  
Digital Research

This paper develops and tests a lifecycle model for the preservation of research data by investigating the research practices of scientists.  This research is based on a mixed-method approach.  An initial study was conducted using case study analytical techniques; insights from these case studies were combined with grounded theory in order to develop a novel model of the Digital Research Data Lifecycle.  A broad-based quantitative survey was then constructed to test and extend the components of the model.  The major contribution of these research initiatives are the creation of the Digital Research Data Lifecycle, a data lifecycle that provides a generalized model of the research process to better describe and explain both the antecedents and barriers to preservation.  The antecedents and barriers to preservation are data management, contextual metadata, file formats, and preservation technologies.  The availability of data management support and preservation technologies, the ability to create and manage contextual metadata, and the choices of file formats all significantly effect the preservability of research data.

scholarly journals Supporting FAIR data: categorization of research data as a tool in data management

2018 ◽  
Vol 37 (4) ◽  
Author(s):  
Jessica Parland-von Essen ◽  
Katja Fält ◽  
Zubair Maalick ◽  
Miika Alonen ◽  
Eduardo Gonzalez
Keyword(s):  
Data Management ◽  
Research Data ◽  
Data Types ◽  
Specific Research ◽  
Research Results ◽  
Data Services ◽  
Operational Data

The demand for implementation of the FAIR data principles is in many cases difficult for a researcher to adhere to in efficient ways due to lacking tools. We suggest categorizing data in a more extensive and systematic way with focus on the inherent properties of the data as means to enhancing research data services. After discussing different approaches to categorizing data, we propose a tripartite research data categorization based around the inherent aspect of stability. The three research data types are operational data, generic research data and research data publications. Generic research data is validated data and can be cumulative, i.e. data can be added without versioning, however if it is dynamic it should be versioned. Generic research data should be separated from immutable dataset publications that are published for reasons of reproducibility of specific research results.

scholarly journals Research data management in Turkey: perceptions and practices

2017 ◽  
Vol 35 (2) ◽  
pp. 271-289 ◽  
Author(s):  
Arsev Umur Aydinoglu ◽  
Guleda Dogan ◽  
Zehra Taskin
Keyword(s):  
Data Management ◽  
Online Survey ◽  
Management Practices ◽  
Cost Effective ◽  
Science Research ◽  
Research Data ◽  
Content Type ◽  
Research Data Management ◽  
Data Practices ◽  
The Subject

Purpose The massive increase in research data being produced nowadays has highlighted the importance of research data management (RDM) to science. Research data not only have to be cost effective but also reliable, discoverable, accessible, and reusable. In this regard, the purpose of this paper is to investigate the perceptions and practices of Turkish researchers on the subject of RDM. Design/methodology/approach An online survey was distributed to the academicians in 25 universities in Turkey, and 532 responses were gathered. Findings Results indicate that although Turkish researchers are aware of the benefits of data management, are willing to share their research data with certain groups, and have decent preservation habits, they express that they lack the technical skills and knowledge needed for RDM. In addition, no institutionalized support (staff, training, software, and hardware) is provided to researchers. Research limitations/implications A well-structured data strategy or policy that includes resource allocation (awareness, training, software/hardware) and is supported by Turkish research agencies is required for better data management practices among researchers in Turkey. Originality/value This is the first study that investigates the data practices of Turkish academics who produce around 30,000 scientific articles annually that are indexed by Web of Science. It contributes to the growing literature on RDM.

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