SERVICE, CONSULTING AND TRAINING: PORTFOLIO EXPANSION TO SUPPORT RESEARCH DATA MANAGEMENT

Abstract University libraries have archaeologically augmented scientific research by collecting, organizing, maintaining, and availing research materials for access. Researchers reckon that with the expertise acquired from conventional cataloging, classification, and indexing coupled with that attained in the development, along with the maintenance of institutional repositories, it is only rational that libraries take a dominant and central role in research data management and further their capacity as curators. Accordingly, University libraries are expected to assemble capabilities, to manage and provide research data for sharing and reusing efficiently. This study examined research librarians’ experiences of RDM activities at the UON Library to recommend measures to enhance managing, sharing and reusing research data. The study was informed by the DCC Curation lifecycle model and the Community Capability Model Framework (CCMF) that enabled the Investigator to purposively capture qualitative data from a sample of 5 research librarians at the UON Library. The data was analysed thematically to generate themes that enabled the Investigator to address the research problem. Though the UON Library had policies on research data, quality assurance and intellectual property, study findings evidenced no explicit policies to guide each stage of data curation and capabilities. There were also inadequacies in skills and training capability, technological infrastructure and collaborative partnerships. Overall, RDM faced challenges in all the examined capabilities. These challenges limited the managing, sharing, and reusing of research data. The study recommends developing an RDM unit within the UON Library to oversee the implementation of RDM activities by assembling all the needed capabilities (policy guidelines, skills and training, technological infrastructure and collaborative partnerships) to support data curation activities and enable efficient managing, sharing and reusing research data.

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Towards a Unified University Infrastructure: The Data Management Roll-Out at the University of Oxford

International Journal of Digital Curation ◽

10.2218/ijdc.v8i2.287 ◽

2013 ◽

Vol 8 (2) ◽

pp. 235-246 ◽

Cited By ~ 6

Author(s):

James A. J. Wilson ◽

Paul Jeffreys

Keyword(s):

Data Management ◽

Research Data ◽

Management Policy ◽

Research Information ◽

Institutional Level ◽

Research Data Management ◽

University Of Oxford ◽

The University ◽

And Training ◽

Roll Out

Since presenting a paper at the International Digital Curation Conference 2010 conference entitled ‘An Institutional Approach to Developing Research Data Management Infrastructure’, the University of Oxford has come a long way in developing research data management (RDM) policy, tools and training to address the various phases of the research data lifecycle. Work has now begun on integrating these various elements into a unified infrastructure for the whole university, under the aegis of the Data Management Roll-out at Oxford (Damaro) Project.This paper will explain the process and motivation behind the project, and describes our vision for the future. It will also introduce the new tools and processes created by the university to tie the individual RDM components together. Chief among these is the ‘DataFinder’ – a hierarchically-structured metadata cataloguing system which will enable researchers to search for and locate research datasets hosted in a variety of different datastores from institutional repositories, through Web 2 services, to filing cabinets standing in department offices. DataFinder will be able to pull and associate research metadata from research information databases and data management plans, and is intended to be CERIF compatible. DataFinder is being designed so that it can be deployed at different levels within different contexts, with higher-level instances harvesting information from lower-level instances enabling, for example, an academic department to deploy one instance of DataFinder, which can then be harvested by another at an institutional level, which can then in turn be harvested by another at a national level.The paper will also consider the requirements of embedding tools and training within an institution and address the difficulties of ensuring the sustainability of an RDM infrastructure at a time when funding for such endeavours is limited. Our research shows that researchers (and indeed departments) are at present not exposed to the true costs of their (often suboptimal) data management solutions, whereas when data management services are centrally provided the full costs are visible and off-putting. There is, therefore, the need to sell the benefits of centrally-provided infrastructure to researchers. Furthermore, there is a distinction between training and services that can be most effectively provided at the institutional level, and those which need to be provided at the divisional or departmental level in order to be relevant and applicable to researchers. This is being addressed in principle by Oxford’s research data management policy, and in practice by the planning and piloting aspects of the Damaro Project.

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PROVIDING RESEARCH DATA MANAGEMENT SERVICES AND PRACTICES AT PDDI-LIPI: PREPAREDNESS, ROLES, CHALLENGES, AND TRAINING

BACA JURNAL DOKUMENTASI DAN INFORMASI ◽

10.14203/j.baca.v41i2.707 ◽

2020 ◽

Vol 41 (2) ◽

pp. 169

Author(s):

Hermin Triasih ◽

Rahmi Rahmi ◽

Katrin Setio Devi

Keyword(s):

Human Resources ◽

Data Management ◽

Online Survey ◽

Training Needs ◽

Research Data ◽

Management Planning ◽

Data Archiving ◽

Research Data Management ◽

And Training ◽

Management Services

This study aims to analyse the implementation of RDM at PDDI-LIPI and to assess its staff’s understanding about RDM services. This article also discusses the challenges and obstacles PDDI faces in providing RDM services. The data was collected via an online survey from 28 July to 7 August 2020. The survey consisted of 35 questions and was shared with 36 respondents via social media. The results identified categories such as research data management services, data management planning services, data archiving services, funding, and staff competency and training needs. In addition, this article also discusses the approach and assessment of RDM services, challenges in providing RDM services, and plans for further developing RDM services at PDDI-LIPI. The results showed that the PDDI staff's understanding of RDM services is adequate. As a new service, the implementation of RDM at PDDI-LIPI continues to develop toward optimisation. RIN is a platform used by PDDI to support this goal. The three biggest obstacles faced by PDDI-LIPI in developing RDM services are limited human resources, competence and budget. Various trainings related to RDM, both sending staff off campus and inviting trainers to campus, were carried out by PDDI to overcome these obstacles. It is recommended to conduct further research on the mapping and upskilling of staff in charge of RDM services.

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Research Data Management Competencies Self-Assessment

10.18122/dataservices.8.boisestate ◽

2021 ◽

Author(s):

Megan Davis ◽

Ellie Dworak ◽

Yitzhak Paul ◽

Elisabeth Shook

Keyword(s):

Data Management ◽

Academic Libraries ◽

Research Data ◽

Management Competencies ◽

Self Assessment ◽

Research Data Management ◽

Support Research

A tool for assessing the competencies of individuals who support Research Data Management (RDM). The tool was developed to help academic libraries bolster skills and services surrounding RDM. This assessment allows the library to better understand and visualize the strengths and gaps in knowledge necessary to effectively run an RDM team.

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Development of a Domain-Specific Ontology to Support Research Data Management for the Tailored Forming Technology

Procedia Manufacturing ◽

10.1016/j.promfg.2020.11.020 ◽

2020 ◽

Vol 52 ◽

pp. 107-112

Author(s):

Tatyana Sheveleva ◽

Oliver Koepler ◽

Iryna Mozgova ◽

Roland Lachmayer ◽

Sören Auer

Keyword(s):

Data Management ◽

Research Data ◽

Domain Specific ◽

Research Data Management ◽

Forming Technology ◽

Tailored Forming ◽

Support Research

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Providing Research Data Management (RDM) Services in Libraries: Preparedness, Roles, Challenges, and Training for RDM Practice

Data and Information Management ◽

10.2478/dim-2019-0009 ◽

2019 ◽

Vol 3 (2) ◽

pp. 84-101 ◽

Cited By ~ 8

Author(s):

Rong Tang ◽

Zhan Hu

Keyword(s):

Data Management ◽

Community Of Practice ◽

Research Data ◽

Institutional Commitment ◽

Research Data Management ◽

Organizational Differences ◽

The Impact ◽

To Receive ◽

Training Opportunities ◽

And Training

Abstract This paper reports the results of an international survey on research data management (RDM) services in libraries. More than 240 practicing librarians responded to the survey and outlined their roles and levels of preparedness in providing RDM services, challenges their libraries face, and knowledge and skills that they deemed essential to advance the RDM practice. Findings of the study revealed not only a number of location and organizational differences in RDM services and tools provided but also the impact of the level of preparedness and degree of development in RDM roles on the types of RDM services provided. Respondents’ perceptions on both the current challenges and future roles of RDM services were also examined. With a majority of the respondents recognizing the importance of RDM and hoping to receive more training while expressing concerns of lack of bandwidth or capacity in this area, it is clear that, in order to grow RDM services, institutional commitment to resources and training opportunities is crucial. As an emergent profession, data librarians need to be nurtured, mentored, and further trained. The study makes a case for developing a global community of practice where data librarians work together, exchange information, help one another grow, and strive to advance RDM practice around the world.

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Research Data Management in an Academic Library

Advances in Library and Information Science - Handbook of Research on Information and Records Management in the Fourth Industrial Revolution ◽

10.4018/978-1-7998-7740-0.ch003 ◽

2021 ◽

pp. 38-55

Author(s):

Chidi Onuoha Kalu ◽

Esther Ihechiluru Chidi-Kalu ◽

Titilola Abigail Mafe

Keyword(s):

Data Management ◽

Academic Libraries ◽

Academic Library ◽

Research Data ◽

The Other ◽

Research Data Management ◽

Other Hand ◽

Support Research

Academic libraries need to store, preserve, and manage scholars' intellectual output, hence the importance of research data management in academic libraries. This chapter focuses on research data management in academic libraries, and it aims at examining the concept of research data, which is referred to as the evidence used to inform or support research conclusions, while data management, on the other hand involves planning for and creating data, organizing, structuring, and documenting data, backing up and storing data, and preparing data for analysis to share with others or to preserve for the long-term.

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Research Data Management Practices at Bindura University of Science Education

Advances in Library and Information Science - Handbook of Research on Information and Records Management in the Fourth Industrial Revolution ◽

10.4018/978-1-7998-7740-0.ch004 ◽

2021 ◽

pp. 56-66

Author(s):

Bvumai Musarurwa

Keyword(s):

Science Education ◽

Data Management ◽

Quantitative Data ◽

Management Practices ◽

Research Data ◽

International Standards ◽

Research Data Management ◽

Policy Guideline ◽

Data Lifecycle ◽

And Training

The study assessed the research data management (RDM) practices at Bindura University of Science Education (BUSE) with the aim of understanding how research data (RD) is managed. The study was prompted by lack of proper RDM policy. UK data archive research data lifecycle model was adopted in the study for benchmarking RDM practices at BUSE in line with international standards. The research used the interpretism approach and is qualitative in nature. Interviews were used to collect qualitative data from the Research and Postgraduate Centre (RPGC), deputy librarian, sub-librarian, and technology librarian. Quantitative data obtained from departmental chairpersons, assistant librarians, and chief library assistant was gathered by using questionnaires. The population was chosen using purposive sampling. The findings revealed that although respondents appreciated RDM practices, some researchers were managing their RD while RPGC was responsible for RD submitted to their office. The concept of RDM was relatively new to most researchers. The study recommended a policy guideline and training of researchers.

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A Spider, an Octopus, or an Animal Just Coming into Existence? Designing a Curriculum for Librarians to Support Research Data Management

Journal of eScience Librarianship ◽

10.7191/jeslib.2014.1055 ◽

2014 ◽

Vol 3 (1) ◽

Cited By ~ 4

Author(s):

Andrew Cox ◽

◽

Eddy Verbaan ◽

Barbara Sen

Keyword(s):

Data Management ◽

Research Data ◽

Research Data Management ◽

Support Research

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Essentials for Data Support: Training the Front Office

International Journal of Digital Curation ◽

10.2218/ijdc.v10i1.364 ◽

2015 ◽

Vol 10 (1) ◽

pp. 240-248 ◽

Cited By ~ 2

Author(s):

Marjan Grootveld ◽

Ellen Verbakel

Keyword(s):

Data Management ◽

Digital Preservation ◽

Research Data ◽

Lessons Learned ◽

Online Resources ◽

Research Data Management ◽

Data Support ◽

Front Office ◽

Library Staff ◽

And Training

At the end of 2011 a Data Intelligence 4 Librarians course was developed to provide online resources and training for digital preservation practitioners, specifically library staff. Lessons learned during the first rounds of the course and developments in the Research Data Management landscape have led to a revision of the positioning, the structure and the content of the course. This paper describes both the three main drivers for the revision, the changes themselves and the lessons that can be drawn from them, after three training rounds in 2014 in the revised format under the new programmatic title of Essentials 4 Data Support.

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