Research Data Management as an Integral Part of the Research Process of Empirical Disciplines Using Landscape Ecology as an Example

Although research institutions take on increased responsibility for providing infrastructures and services around the proper handling of research data, there is no comprehensive framework addressing the ideal conditions of this implementation process. To overcome this gap, we present the DIAMANT model, a reference model aimed at providing an orientation framework for the implementation of research data management guided by the research process itself. It builds upon a central research data management information unit controlling the information flow between all other organizational units involved in research data management. Due to the possibility of outsourcing organizational units, the implementation process is maximally flexible and efficient.

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Research Data Management: A proposed framework to boost research in Higher Educational Institutes.

IASSIST Quarterly ◽

10.29173/iq12 ◽

2017 ◽

Vol 41 (1-4) ◽

pp. 12

Author(s):

Bhojaraju Gunjal ◽

Panorea Gaitanou

Keyword(s):

Literature Review ◽

Best Practices ◽

Data Management ◽

Skill Development ◽

Research Process ◽

Research Data ◽

Research Data Management ◽

Research Activities ◽

Educational Institute ◽

Higher Educational

This paper attempts to present a brief overview of several Research Data Management (RDM) issues and a detailed literature review regarding the RDM aspects adopted in libraries globally. Furthermore, it will describe several tendencies concerning the management of repository tools for research data, as well as the challenges in implementing the RDM. The proper planned training and skill development for all stakeholders by mentors to train both staff and users are some of the issues that need to be considered to enhance the RDM process. An effort will be also made to present the suitable policies and workflows along with the adoption of best practices in RDM, so as to boost the research process in an organisation. This study will showcase the implementation of RDM processes in the Higher Educational Institute of India, referring particularly to the Central Library @ NIT Rourkela in Odisha, India with a proposed framework. Finally, this study will also propose an area of opportunities that can boost research activities in the Institute.

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Implementação de serviços institucionais de administração de dados | Implementation of Institutional Data Stewardship Services

Liinc em Revista ◽

10.18617/liinc.v15i2.4819 ◽

2019 ◽

Vol 15 (2) ◽

Author(s):

Paloma Marín-Arraiza ◽

Silvana Vidotti

Keyword(s):

Data Management ◽

Research Process ◽

Research Data ◽

Research Support ◽

Research Data Management ◽

Institutional Services ◽

Bibliographic Search ◽

Data Stewardship ◽

Data Policy ◽

High Production

RESUMO As tarefas de gestão de dados de pesquisa ao longo do processo de pesquisa têm se tornado muito importantes devido à alta produção de dados e à exigência da sua preservação. Tanto bibliotecas quanto seções de apoio à pesquisa de diversas instituições de ensino e pesquisa têm começado a implementar serviços para a gestão de dados e a profissionalização desta gestão. Com um caráter qualitativo, e após um levantamento bibliográfico em bases de dados abertas, contextualiza-se a gestão de dados de pesquisa, analisam-se os perfis profissionais e determinam-se três fases para a implementação institucional destes serviços: elaboração de uma política, estabelecimento de uma unidade de informação e integração de profissionais da gestão de dados.Palavras-chave: Administração de Dados; Dados de Pesquisa; Gestão de Dados de Pesquisa; Política de Dados; Serviços Institucionais. ABSTRACT The tasks of managing research data throughout the research process have become very important due to the high production of data and the requirement for its preservation. Both libraries and research support sections of various research institutions have started to implement services for data management and the professionalization of this management. With a qualitative character, and after a bibliographic search in open databases, research data management is contextualized, professional profiles are analyzed, and three phases are determined for the institutional implementation of these services: the elaboration of a policy, the establishment of an information unit and the integration of data management professionals.Keywords: Data Stewardship; Research Data; Research Data Management; Data Policy; Institutional Services.

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Research data management practices of chemistry researchers in federal universities of technology in Nigeria

Digital Library Perspectives ◽

10.1108/dlp-06-2020-0051 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Fatimah Jibril Abduldayan ◽

Fasola Petunola Abifarin ◽

Georgina Uchey Oyedum ◽

Jibril Attahiru Alhassan

Keyword(s):

Data Management ◽

Management Practices ◽

Management Practice ◽

Research Process ◽

Management Plan ◽

Research Data ◽

Content Type ◽

Data Preservation ◽

Research Data Management ◽

Research Findings

Purpose The purpose of this study was to understand the research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Appropriate research data management practice ensures that research data are available for reuse by secondary users, and research findings can be verified and replicated within the scientific community. A poor research data management practice can lead to irrecoverable data loss, unavailability of data to support research findings and lack of trust in the research process. Design/methodology/approach An exploratory research technique involving semi-structured, oral and face-to-face interview is used to gather data on research data management practices of chemistry researchers in Nigeria. Interview questions were divided into four major sections covering chemistry researchers’ understanding of research data, experience with data loss, data storage method and backup techniques, data protection, data preservation and availability of data management plan. Braun and Clarke thematic analysis approach was adapted, and the Provalis Qualitative Data Miner (version 5) software was used for generating themes and subthemes from the coding framework and for presenting the findings. Findings Findings revealed that chemistry researchers in Nigeria have a good understanding of the concept of research data and its importance to research findings. Chemistry researchers have had several experiences of irrecoverable loss of data because of poor choice of storage devices, back-up methods and weak data protection systems. Even though the library was agreed as the most preferred place for long-term data preservation, there is the issue of trust and fear of loss of ownership of data to unauthorized persons or party. No formal data management plan is used while conducting their scientific research. Research limitations/implications The research focused on research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Although the findings of the study are similar to perceptions and practices of researchers around the world, it cannot be used as a basis for generalization across other scientific disciplines. Practical implications This study concluded that chemistry researchers need further orientation and continuous education on the importance and benefits of appropriate research data management practice. The library should also roll out research data management programs to guide researchers and improve their confidence throughout the research process. Social implications Appropriate research data management practice not only ensures that the underlying research data are true and available for reuse and re-validation, but it also encourages data sharing among researchers. Data sharing will help to ensure better collaboration among researchers and increased visibility of the datasets and data owners through the use of standard data citations and acknowledgements. Originality/value This is a qualitative and in-depth study of research data management practices and perceptions among researchers in a particular scientific field of study.

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Research Data Sharing and Reuse Through Open Data

Advances in Library and Information Science - Open Access Implications for Sustainable Social, Political, and Economic Development ◽

10.4018/978-1-7998-5018-2.ch015 ◽

2021 ◽

pp. 284-306

Author(s):

Abel Christopher M'kulama ◽

Akakandelwa Akakandelwa

Keyword(s):

Data Management ◽

Data Sharing ◽

Data Storage ◽

Mixed Methods Research ◽

Open Data ◽

Research Process ◽

Research Data ◽

Research Data Management ◽

Inadequate Knowledge ◽

Self Administered Questionnaire

Research data management is considered a critical step in the research process among researchers. Researchers are required to submit RDM plans with details about data storage, data sharing, and reuse procedures when submitting research proposals for grants. This chapter presents findings of an investigation into the perceptions and practices of ZARI researchers towards research data management. Mixed methods research using a self-administered questionnaire was adopted for data collection. Fifty-one researchers were sampled and recruited for participation into the study. The study established that the majority of the researchers were not depositing their research data in central repositories; data was kept on individual's devices and was therefore not readily available for sharing. The major challenges being faced by researchers included lack of a policy, lack of a repository, and inadequate knowledge in RDM. The study concludes that research data at ZARI was not being professionally managed. The study recommends for formulation of policies, establishment of repository and staff training.

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Defining the role of libraries in the Open Science landscape: a reflection on current European practice

Open Information Science ◽

10.1515/opis-2018-0001 ◽

2018 ◽

Vol 2 (1) ◽

pp. 1-22 ◽

Cited By ~ 1

Author(s):

Paul Ayris ◽

Tiberius Ignat

Keyword(s):

Open Access ◽

Data Management ◽

Case Studies ◽

Publishing Research ◽

Research Process ◽

Open Science ◽

Research Data ◽

Step Test ◽

Open Access Publishing ◽

Research Data Management

Abstract This collaborative paper looks at how libraries can engage with and offer leadership in the Open Science movement. It is based on case studies and the results of an EU-funded research project on Research Data Management taken from European research-led universities and their libraries. It begins by analysing three recent trends in Science, and then links component parts of the research process to aspects of Open Science. The paper then looks in detail at four areas and identifies roles for libraries: Open Access and Open Access publishing, Research Data Management, E-Infrastructures (especially the European Open Science Cloud), and Citizen Science. The paper ends in suggesting a model for how libraries, by using a 4-step test, can assess their engagement with Open Science. This 4-step test is based on lessons drawn from the case studies.

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A critical analysis of lifecycle models of the research process and research data management

Aslib Journal of Information Management ◽

10.1108/ajim-11-2017-0251 ◽

2018 ◽

Vol 70 (2) ◽

pp. 142-157 ◽

Cited By ~ 12

Author(s):

Andrew Martin Cox ◽

Winnie Wan Ting Tam

Keyword(s):

Data Management ◽

Design Methodology ◽

Research Process ◽

Research Data ◽

Systematic Analysis ◽

Content Type ◽

Research Data Management ◽

Library And Information Studies ◽

Information Studies ◽

Practical Implications

Purpose Visualisations of research and research-related activities including research data management (RDM) as a lifecycle have proliferated in the last decade. The purpose of this paper is to offer a systematic analysis and critique of such models. Design/methodology/approach A framework for analysis synthesised from the literature presented and applied to nine examples. Findings The strengths of the lifecycle representation are to clarify stages in research and to capture key features of project-based research. Nevertheless, their weakness is that they typically mask various aspects of the complexity of research, constructing it as highly purposive, serial, uni-directional and occurring in a somewhat closed system. Other types of models such as spiral of knowledge creation or the data journey reveal other stories about research. It is suggested that we need to develop other metaphors and visualisations around research. Research limitations/implications The paper explores the strengths and weaknesses of the popular lifecycle model for research and RDM, and also considers alternative ways of representing them. Practical implications Librarians use lifecycle models to explain service offerings to users so the analysis will help them identify clearly the best type of representation for particular cases. The critique offered by the paper also reveals that because researchers do not necessarily identify with a lifecycle representation, alternative ways of representing research need to be developed. Originality/value The paper offers a systematic analysis of visualisations of research and RDM current in the Library and Information Studies literature revealing the strengths and weaknesses of the lifecycle metaphor.

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A map of Research Data in Egypt … Towards a Strategic Management

ARID International Journal of Informetrics ◽

10.36772/arid.aijisc.2021.221 ◽

2021 ◽

pp. 7-58

Author(s):

شريف كامل شاهين

Keyword(s):

Data Management ◽

National Level ◽

Research Process ◽

Research Data ◽

Research Institutions ◽

Research Data Management ◽

Global Trend ◽

Management Plans ◽

Donor Agencies ◽

Interest In Research

The world is experiencing unprecedented interest in Research Data Management (RDM), on three levels: the level of individual researchers themselves, the level of research institutions, and the national level. The researcher believes that there are three main reasons or motives behind interest in RDM, firstly to make most of the efforts and other resources and data collected for the benefit of several researches that share the target data with different dimensions, angles and methods of research. Secondly, Information technology also provides tools and software that facilitate most of the collection, organization, preservation, retrieval, documentation and insurance of data required for research projects in different fields and communities. Thirdly, the global trend of what is known as bibliometrics, altmetrics analytics and others. In fact, most of these research data analytics provide global indicators related to researchers and their research from several angles or dimensions, and take several forms, including: reports, lists and statistical sites either in specific areas of knowledge, or at a specific regional or global level without boundaries. It is now clear and announced by most donor agencies and institutions that financial support for research should ensure and ensure the successful management of research data at most stages of research as a prerequisite for obtaining grants, both during the research process and after completion. In this exploratory paper, which explores many international experiences and expertise in the field of research data management plans, the researcher is subjected to a precise inventory of research institutions in Egypt, whatever their names, fields, or administrative dependencies (universities, ministries, independent centers ...).

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Supporting Research Data Management and Open Science in Academic Libraries: a Data Librarian’s View

Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare ◽

10.31263/voebm.v72i2.3303 ◽

2019 ◽

Vol 72 (2) ◽

pp. 263-273

Author(s):

Robin Rice

Keyword(s):

Data Management ◽

Information Overload ◽

Research Process ◽

Open Science ◽

Research Data ◽

Academic Librarians ◽

Comfort Zone ◽

Research Data Management ◽

Traditional Work ◽

Library Profession

The ‘data revolution’ has impacted researchers across the disciplines. As if the traditional work of teaching, competing for grants and promotion, doing research and publishing results was not challenging enough, researchers are required to make fundamental changes in the way they do all of these things. A similar shift can be seen for academic librarians. Librarians who were taught to meet the needs of their users based on information scarcity now need to retrain themselves to help users deal with information overload. Moreover, librarians increasingly find themselves ‘upstream’ in the research process, trying to assist their users in managing unwieldy amounts of data when their comfort zone is firmly ‘downstream’ in the post-publication stage. Unsettling as it may be, these are exciting developments for the library profession.

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The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽

10.1093/gigascience/giaa107 ◽

2020 ◽

Vol 9 (10) ◽

Cited By ~ 1

Author(s):

Daniel Arend ◽

Patrick König ◽

Astrid Junker ◽

Uwe Scholz ◽

Matthias Lange

Keyword(s):

Data Management ◽

Data Storage ◽

Best Practice ◽

Research Process ◽

Research Data ◽

Primary Data ◽

Data Repository ◽

Plant Genomics ◽

Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

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