Archives des mots-clés : research data

Multi-Stakeholder Research Data Management Training as a Tool to Improve the Quality, Integrity, Reliability and Reproducibility of Research

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Author : Jukka Rantasaari

To ensure the quality and integrity of data and the reliability of research, data must be well documented, organised, and described. This calls for research data management (RDM) education for researchers.

In light of 3 ECTS Basics of Research Data Management (BRDM) courses held between 2019 and 2021, we aim to find how a generic level multi-stakeholder training can improve STEM and HSS disciplines’ doctoral students’ and postdoc researchers’ competencies in RDM. The study uses quantitative, descriptive and inferential statistics to analyse respondents’ self-ratings of their competencies, and a qualitative grounded theory-inspired approach to code and analyse course participants’ feedback.

Results: On average, based on the post-course surveys, respondents’ (n = 123) competencies improved one point on a four-level scale, from “little competence” (2) to “somewhat competent” (3). Participants also reported that the training would change their current practices in planning research projects, data management and documentation, acknowledging legal and data privacy viewpoints, and data collecting and organising.

Participants indicated that it would be helpful to see legal and data privacy principles and regulations presented as concrete instructions, cases, and examples. The most requested continuing education topics were metadata and description, discipline specific cultures, and backup, version management, and storage.

Conclusions: Regarding to the widely used criteria for successful training containing 1) active participation during training; 2) demand for RDM training; 3) increased participants’ knowledge and understanding of RDM and confidence in enacting RDM practices; and 4) positive post-training feedback, BRDM meets the criteria.

This study shows that although reaching excellent competence in a RDM basics training is improbable, participants become aware of RDM and its contents and gain the elementary tools and basic skills to begin applying sound RDM practices in their research.

Furthermore, participants are introduced to the academic and research support professionals and vice versa: Stakeholders will get to know the challenges that young researchers and research students encounter when applying RDM. The study reveals valuable information on doctoral students’ and postdoc researchers’ competencies, the impact of education on competencies, and further learning needs in RDM.

URL : Multi-Stakeholder Research Data Management Training as a Tool to Improve the Quality, Integrity, Reliability and Reproducibility of Research

DOI : https://doi.org/10.53377/lq.11726

The financial maintenance of social science data archives: Four case studies of long-term infrastructure work

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Authors : Kristin R. Eschenfelder, Kalpana Shankar, Greg Downey

Contributing to the literature on knowledge infrastructure maintenance, this article describes a historical longitudinal analysis of revenue streams employed by four social science data organizations: the Roper Center for Public Opinion, the Inter-university Consortium for Political and Social Research (ICPSR), the UK Data Archive (UKDA), and the LIS Cross-National Data Center in Luxembourg (LIS).

Drawing on archival documentation and interviews, we describe founders’ assumptions about revenue, changes to revenue streams over the long term, practices for developing and maintaining revenue streams, the importance of financial support from host organizations, and how the context of each data organization shaped revenue possibilities.

We extend conversations about knowledge infrastructure revenue streams by showing the types of change that have occurred over time and how it occurs. We provide examples of the types of flexibility needed for data organizations to remain sustainable over 40–60 years of revenue changes.

We distinguish between Type A flexibilities, or development of new products and services, and Type B flexibilities, or continuous smaller adjustments to existing revenue streams. We argue that Type B flexibilities are as important as Type A, although they are easily overlooked. Our results are relevant to knowledge infrastructure managers and stakeholders facing similar revenue challenges.

URL : The financial maintenance of social science data archives: Four case studies of long-term infrastructure work

DOI : https://doi.org/10.1002/asi.24691

Practices Before Policy: Research Data Management Behaviours in Canada

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Authors : Melissa Cheung, Alexandra Cooper, Dylanne Dearborn, Elizabeth Hill, Erin Johnson, Marjorie Mitchell, Kristi Thompson

In anticipation of the then forthcoming Tri-Agency Research Data Management Policy, a consortium of professionals from Canadian university libraries surveyed researchers on their research data management (RDM) practices, attitudes, and interest in data management services.

Data collected from three surveys targeting researchers in science and engineering, humanities and social sciences, and health sciences and medicine were compiled to create a national dataset.

The present study is the first large-scale survey investigating researcher RDM practices in Canada, and one of the few recent multi-institutional and multidisciplinary surveys on this topic.

This article presents the results of the survey to assess researcher readiness to meet RDM policy requirements, namely the preparation of data management plans (DMPs) and data deposit in a digital repository.

The survey results also highlight common trends across the country while revealing differences in practices and attitudes between disciplines. Based on our survey results, most researchers would have to change their RDM behaviors to meet Tri-Agency RDM policy requirements.

The data we gathered provides insights that can help institutions prioritize service development and infrastructure that will meet researcher needs.

URL : Practices Before Policy: Research Data Management Behaviours in Canada

DOI : https://doi.org/10.21083/partnership.v17i1.6779

Open research data: A case study into institutional and infrastructural arrangements to stimulate open research data sharing and reuse

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Authors : Thijmen van Gend, Anneke Zuiderwijk

This study investigates which combination of institutional and infrastructural arrangements positively impact research data sharing and reuse in a specific case. We conducted a qualitative case study of the institutional and infrastructural arrangements implemented at Delft University of Technology in the Netherlands.

In the examined case, it was fundamental to change the mindset of researchers and to make them aware of the benefits of sharing data. Therefore, arrangements should be designed bottom-up and used as a “carrot” rather than as a “stick.” Moreover, support offered to researchers should cover at least legal, financial, administrative, and practical issues of research data management and should be informal in nature.

Previous research describes generic institutional and infrastructural instruments that can stimulate open research data sharing and reuse. This study is among the first to analyze what and how infrastructural and institutional arrangements work in a particular context. It provides the basis for other scholars to study such arrangements in different contexts.

Open data policymakers, universities, and open data infrastructure providers can use our findings to stimulate data sharing and reuse in practice, adapted to the contextual situation. Our study focused on a single case and a particular part of the university.

We recommend repeating this research in other contexts, that is, at other universities, faculties, and involving other research data infrastructure providers.

URL : Open research data: A case study into institutional and infrastructural arrangements to stimulate open research data sharing and reuse

DOI : https://doi.org/10.1177/09610006221101200

Le positionnement des bibliothèques universitaires et de recherche françaises dans les politiques publiques des données de la recherche

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Auteur/Author : Paul Cormier

A l’heure du quatrième paradigme de la science, la science ouverte, et la gestion des données de la recherche en particulier, font désormais l’objet de politiques qui se structurent à différentes échelles (internationale, européenne, nationale et au sein des établissements universitaires et de recherche).

Après une phase initiale d’interrogations, il apparaît désormais que les bibliothèques sont des actrices et des partenaires cruciales tant en ce qui concerne le leadership que les questions techniques dans l’appui à la recherche.

Elles sont aujourd’hui présentes et actives dans la grande majorité des espaces de réflexion autour de ces enjeux. Adossé à la sociologie de l’action publique, ce mémoire entend dépasser la question du « pourquoi » et du questionnement autour de la légitimité des bibliothèques à participer à la gestion des données de la recherche en s’interrogeant sur le « comment ».

Ce travail identifie trois rôles exercés par les bibliothèques dans le cadre leur participation à l’élaboration des politiques des données de la recherche (rôles d’expertes, de conception et d’actrices opérationnelles).

Il montre que c’est d’abord en élargissant les réseaux professionnels français puis en mobilisant et en structurant leur discours à travers leurs organisations professionnelles, par leur capacité à travailler en réseau, leur expertise technique, leur expérience tirée du déploiement de l’open access et leur capacité d’advocacy, que les bibliothèques ont su se placer en actrices incontournables du chantier de la science ouverte.

URL : Le positionnement des bibliothèques universitaires et de recherche françaises dans les politiques publiques des données de la recherche

Original location : https://www.enssib.fr/bibliotheque-numerique/notices/70658-le-positionnement-des-bibliotheques-universitaires-et-de-recherche-francaises-dans-les-politiques-publiques-des-donnees-de-la-recherche

The Role of Data in an Emerging Research Community : Environmental Health Research as an Exemplar

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Authors : Danielle Polloc, An Yan, Michelle Parker, Suzie Allard

Open science data benefit society by facilitating convergence across domains that are examining the same scientific problem. While cross-disciplinary data sharing and reuse is essential to the research done by convergent communities, so far little is known about the role data play in how these communities interact.

An understanding of the role of data in these collaborations can help us identify and meet the needs of emerging research communities which may predict the next challenges faced by science. This paper represents an exploratory study of one emerging community, the environmental health community, examining how environmental health research groups form, collaborate, and share data.

Five key insights about the role of data in emerging research communities are identified and suggestions are made for further research.

URL : The Role of Data in an Emerging Research Community : Environmental Health Research as an Exemplar

DOI : https://doi.org/10.2218/ijdc.v16i1.653

Globally Accessible Distributed Data Sharing (GADDS): a decentralized FAIR platform to facilitate data sharing in the life sciences

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Authors : Pavel Vazquez, Kayoko Hirayama-Shoji, Steffen Novik, Stefan Krauss, Simon Rayner

Motivation

Technical advances have revolutionized the life sciences and researchers commonly face challenges associated with handling large amounts of heterogeneous digital data. The Findable, Accessible, Interoperable and Reusable (FAIR) principles provide a framework to support effective data management.

However, implementing this framework is beyond the means of most researchers in terms of resources and expertise, requiring awareness of metadata, policies, community agreements, and other factors such as vocabularies and ontologies.

Results

We have developed the Globally Accessible Distributed Data Sharing (GADDS) platform to facilitate FAIR-like data-sharing in cross-disciplinary research collaborations. The platform consists of (i) a blockchain based metadata quality control system, (ii) a private cloud-like storage system and (iii) a version control system. GADDS is built with containerized technologies, providing minimal hardware standards and easing scalability, and offers decentralized trust via transparency of metadata, facilitating data exchange and collaboration.

As a use case, we provide an example implementation in engineered living material technology within the Hybrid Technology Hub at the University of Oslo.

URL : Globally Accessible Distributed Data Sharing (GADDS): a decentralized FAIR platform to facilitate data sharing in the life sciences

DOI : https://doi.org/10.1093/bioinformatics/btac362