scholarly journals Research Librarians’ Experiences of Research Data Management Activities at an Academic Library in a Developing Country

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Johnson Masinde ◽  
Jing Chen ◽  
Daniel Wambiri ◽  
Angela Mumo
Keyword(s):  
Data Management ◽  
Academic Library ◽  
Research Data ◽  
Data Curation ◽  
Collaborative Partnerships ◽  
University Libraries ◽  
Model Framework ◽  
Technological Infrastructure ◽  
Research Data Management ◽  
And Training

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.

scholarly journals Researchers' Perceptions of Research Data Management Activities at an Academic Library in a Developing Country

2021 ◽  
Vol 10 (2) ◽  
pp. 1-17
Author(s):  
Johnson Mulongo Masinde ◽  
Jing Chen ◽  
Daniel Wambiri Muthee
Keyword(s):  
Cross Section ◽  
Academic Library ◽  
Research Data ◽  
Data Curation ◽  
Collaborative Partnerships ◽  
Technological Infrastructure ◽  
Knowledge And Skills ◽  
Descriptive Research ◽  
Research Data Management ◽  
Broad Cross Section

This study investigated researchers perceptions of RDM at the MGGL to recommend measures to enhance managing, sharing, and reusing data. The study was underpinned by the DCC Curation lifecycle model and the CCMF which enabled the investigator to employ a descriptive research design to purposively capture data from a broad cross-section of 330 researchers. The data was analysed using SPSS to generate descriptive and inferential statistics that enabled the Investigator to answer the problem.Study findings demonstrate no explicit policies to guide each stage of data curation and capabilities. There were also inadequacies in the knowledge and skills capability, technological infrastructure and collaborative partnerships. Overall, RDM faced challenges in all the examined capabilities. These challenges limited managing, sharing, and reusing data.The study recommends establishing a CMU within the MGGL to oversee the implementation of RDM activities by assembling all the needed capabilities to support data curation activities and enable efficient managing, sharing and reusing research data

scholarly journals Researchers’ Perceptions of Research Data Management Activities

2021 ◽  
Vol 10 (2) ◽  
pp. 0-0
Keyword(s):  
Research Design ◽  
Cross Section ◽  
Research Data ◽  
Data Curation ◽  
Collaborative Partnerships ◽  
Technological Infrastructure ◽  
Knowledge And Skills ◽  
Descriptive Research ◽  
Research Data Management ◽  
Broad Cross Section

This study investigated researchers perceptions of RDM at the MGGL to recommend measures to enhance managing, sharing, and reusing data. The study was underpinned by the DCC Curation lifecycle model and the CCMF which enabled the investigator to employ a descriptive research design to purposively capture data from a broad cross-section of 330 researchers. The data was analysed using SPSS to generate descriptive and inferential statistics that enabled the Investigator to answer the problem.Study findings demonstrate no explicit policies to guide each stage of data curation and capabilities. There were also inadequacies in the knowledge and skills capability, technological infrastructure and collaborative partnerships. Overall, RDM faced challenges in all the examined capabilities. These challenges limited managing, sharing, and reusing data.The study recommends establishing a CMU within the MGGL to oversee the implementation of RDM activities by assembling all the needed capabilities to support data curation activities and enable efficient managing, sharing and reusing research data

scholarly journals The CARL Portage Partnership Story

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Charles Humphrey
Keyword(s):  
Data Management ◽  
Academic Library ◽  
Research Data ◽  
Cultural Economic ◽  
Association Of Research Libraries ◽  
Research Data Management ◽  
Transient Nature ◽  
Canadian Association ◽  
Advance Research ◽  
Digital Research

Portage is the research data management initiative of the Canadian Association of Research Libraries and its story has been very much about establishing partnerships in a complex environment to advance research data management services and infrastructure in Canada. Many jurisdictions make up the space in which research data management takes place. A variety of legal, political, cultural, economic, technological, and scientific factors are at play and how they fit together depends on the connections between a number of stakeholders. The levels at which these stakeholders operate and the transient nature of research data itself made the development of partnerships a complex undertaking for Portage. This article describes the building of partnerships in a multi-jurisdictional environment, discusses challenges in operating in Canada's digital research ecosystem, and highlights the importance of working with Canada's regional academic library associations in laying the foundations for digital research infrastructure to support data management. 

scholarly journals Disciplinary differences in faculty research data management practices and perspectives

2013 ◽  
Vol 8 (2) ◽  
pp. 5-26 ◽  
Author(s):  
Katherine G. Akers ◽  
Jennifer Doty
Keyword(s):  
Data Management ◽  
Research University ◽  
Management Practices ◽  
Research Data ◽  
Data Curation ◽  
Academic Librarians ◽  
Disciplinary Differences ◽  
Research Data Management ◽  
Management Actions ◽  
Research Domains

Academic librarians are increasingly engaging in data curation by providing infrastructure (e.g., institutional repositories) and offering services (e.g., data management plan consultations) to support the management of research data on their campuses. Efforts to develop these resources may benefit from a greater understanding of disciplinary differences in research data management needs. After conducting a survey of data management practices and perspectives at our research university, we categorized faculty members into four research domains—arts and humanities, social sciences, medical sciences, and basic sciences—and analyzed variations in their patterns of survey responses. We found statistically significant differences among the four research domains for nearly every survey item, revealing important disciplinary distinctions in data management actions, attitudes, and interest in support services. Serious consideration of both the similarities and dissimilarities among disciplines will help guide academic librarians and other data curation professionals in developing a range of data-management services that can be tailored to the unique needs of different scholarly researchers.

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

2013 ◽  
Vol 8 (2) ◽  
pp. 235-246 ◽  
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.

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

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.

scholarly journals Data literacy for researchers and data librarians

2016 ◽  
Vol 49 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Information Literacy ◽  
Academic Library ◽  
Research Data ◽  
Review Of Literature ◽  
Data Literacy ◽  
Data Intensive ◽  
Research Data Management ◽  
Data Citation

This paper describes data literacy and emphasizes its importance. Data literacy is vital for researchers who need to become data literate science workers and also for (potential) data management professionals. Its important characteristic is a close connection and similarity to information literacy. To support this argument, a review of literature was undertaken on the importance of data, and the data-intensive paradigm of scientific research, researchers’ expected and real behaviour, the nature of research data management, the possible roles of the academic library, data quality and data citation, Besides describing the nature of data literacy and enumerating the related skills, the application of phenomenographic approaches to data literacy and its relationship to the digital humanities have been identified as subjects for further investigation.

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