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

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
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.

scholarly journals Archiving South African digital research data: How ready are we?

2016 ◽  
Vol Volume 112 (Number 7/8) ◽  
Author(s):  
Margaret M. Koopman ◽  
Karin de Jager ◽  
◽  
Keyword(s):  
Data Management ◽  
South African ◽  
Academic Research ◽  
Research Data ◽  
Digital Data ◽  
Systematic Research ◽  
Data Archiving ◽  
Research Data Management ◽  
The University ◽  
Digital Research

Abstract Digital data archiving and research data management have become increasingly important for institutions in South Africa, particularly after the announcement by the National Research Foundation, one of the principal South African academic research funders, recommending these actions for the research that they fund. A case study undertaken during the latter half of 2014, among the biological sciences researchers at a South African university, explored the state of data management and archiving at this institution and the readiness of researchers to engage with sharing their digital research data through repositories. It was found that while some researchers were already engaged with digital data archiving in repositories, neither researchers nor the university had implemented systematic 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.

Designing an information architecture for data management technologies: Introducing the DIAMANT model

2019 ◽  
Vol 52 (2) ◽  
pp. 592-600
Author(s):  
Katarina Blask ◽  
André Förster
Keyword(s):  
Data Management ◽  
Reference Model ◽  
Implementation Process ◽  
Research Process ◽  
Research Data ◽  
Information Architecture ◽  
Central Research ◽  
Research Data Management ◽  
Comprehensive Framework ◽  
The Ideal

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.

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

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.

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. 

Knowledge management, research data management, and university scholarship

VINE ◽  
2015 ◽  
Vol 45 (3) ◽  
pp. 344-359 ◽  
Author(s):  
Joyline Makani
Keyword(s):  
Knowledge Management ◽  
Data Management ◽  
Research Data ◽  
Management Support ◽  
Data Discovery ◽  
Content Type ◽  
Research On Research ◽  
Research Data Management ◽  
Academic Scholarship ◽  
Theoretical Perspectives

Purpose – The purpose of this paper is to synthesize existing research on research data management (RDM), academic scholarship and knowledge management and provide a conceptual framework for an institutional research data management support-system (RDMSS) for systems development, managerial and academic use. Design/methodology/approach – Viewing RDMSS from multiple theoretical perspectives, including data management, knowledge management, academic scholarship and the practice-based perspectives of knowledge and knowing, this paper conceptually explores the systems’ elements needed in the development of an institutional RDM service by considering the underlying data discovery and application issues, as well as the nature of academic scholarship and knowledge creation, discovery, application and sharing motivations in a university environment. Findings – The paper provides general criteria for an institutional RDMSS framework. It suggests that RDM in universities is at the very heart of the knowledge life cycle and is a central ingredient to the academic scholarships of discovery, integration, teaching, engagement and application. Research limitations/implications – This is a conceptual exploration and as a result, the research findings may lack generalisability. Researchers are therefore encouraged to further empirically examine the proposed propositions. Originality/value – The broad RDMSS framework presented in this paper can be compared with the actual situation at universities and eventually guide recommendations for adaptations and (re)design of the institutional RDM infrastructure and knowledge discovery services environment. Moreover, this paper will help to address some of the identified underlying scholarship and RDM disciplinary divides and confusion constraining the effective functioning of the modern day university’s RDM and data discovery environment.

scholarly journals Is Democracy the Right System? Collaborative Approaches to Building an Engaged RDM Community

2017 ◽  
Author(s):  
Marta Teperek ◽  
Rosie Higman ◽  
Danny Kingsley
Keyword(s):  
Data Management ◽  
Community Engagement ◽  
Support Services ◽  
Cost Benefit Analysis ◽  
End Users ◽  
Research Data ◽  
Management Support ◽  
Initial Development ◽  
Positive Effects ◽  
Research Data Management

AbstractWhen developing new products, tools or services, one always need to think about the end users to ensure a wide-spread adoption. While this applies equally to services developed at higher education institutions, sometimes these services are driven by policies and not by needs of end users. This policy-driven approach can prove challenging for building effective community engagement. The initial development of Research Data Management support services at the University of Cambridge was policy-driven and subsequently failed in the first instance to engage the community of researchers for whom these services were created.In this practice paper we will describe the initial approach undertaken at Cambridge when developing RDM services, the results of this approach and lessons learnt. We will then provide an overview of alternative, democratic strategies employed and their positive effects on community engagement. We will summarise by performing a cost-benefit analysis of the two approaches. This paper might be a useful case study for any institutions aiming to develop central support services for researchers, with conclusions applicable to the wide sector, and extending beyond Research Data Management services.

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