Archives des mots-clés : data sharing

Analysis of U.S. Federal Funding Agency Data Sharing Policies 2020 Highlights and Key Observations

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Authors : Reid I. Boehm, Hannah Calkins, Patricia B. Condon, Jonathan Petters, Rachel Woodbrook

Federal funding agencies in the United States (U.S.) continue to work towards implementing their plans to increase public access to funded research and comply with the 2013 Office of Science and Technology memo Increasing Access to the Results of Federally Funded Scientific Research.

In this article we report on an analysis of research data sharing policy documents from 17 U.S. federal funding agencies as of February 2021. Our analysis is guided by two questions: 1.) What do the findings suggest about the current state of and trends in U.S. federal funding agency data sharing requirements? 2.) In what ways are universities, institutions, associations, and researchers affected by and responding to these policies?

Over the past five years, policy updates were common among these agencies and several themes have been thoroughly developed in that time; however, uncertainty remains around how funded researchers are expected to satisfy these policy requirements.

URL : Analysis of U.S. Federal Funding Agency Data Sharing Policies 2020 Highlights and Key Observations

DOI : https://doi.org/10.2218/ijdc.v17i1.791

Data Management Plans: Implications for Automated Analyses

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Authors : Ngoc-Minh Pham, Heather Moulaison-Sandy, Bradley Wade Bishop, Hannah Gunderman

Data management plans (DMPs) are an essential part of planning data-driven research projects and ensuring long-term access and use of research data and digital objects; however, as text-based documents, DMPs must be analyzed manually for conformance to funder requirements.

This study presents a comparison of DMPs evaluations for 21 funded projects using 1) an automated means of analysis to identify elements that align with best practices in support of open research initiatives and 2) a manually-applied scorecard measuring these same elements.

The automated analysis revealed that terms related to availability (90% of DMPs), metadata (86% of DMPs), and sharing (81% of DMPs) were reliably supplied. Manual analysis revealed 86% (n = 18) of funded DMPs were adequate, with strong discussions of data management personnel (average score: 2 out of 2), data sharing (average score 1.83 out of 2), and limitations to data sharing (average score: 1.65 out of 2).

This study reveals that the automated approach to DMP assessment yields less granular yet similar results to manual assessments of the DMPs that are more efficiently produced. Additional observations and recommendations are also presented to make data management planning exercises and automated analysis even more useful going forward.

URL : Data Management Plans: Implications for Automated Analyses

DOI : http://doi.org/10.5334/dsj-2023-002

A focus groups study on data sharing and research data management

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Authors : Devan Ray Donaldson, Joshua Wolfgang Koepke

Data sharing can accelerate scientific discovery while increasing return on investment beyond the researcher or group that produced them. Data repositories enable data sharing and preservation over the long term, but little is known about scientists’ perceptions of them and their perspectives on data management and sharing practices.

Using focus groups with scientists from five disciplines (atmospheric and earth science, computer science, chemistry, ecology, and neuroscience), we asked questions about data management to lead into a discussion of what features they think are necessary to include in data repository systems and services to help them implement the data sharing and preservation parts of their data management plans.

Participants identified metadata quality control and training as problem areas in data management. Additionally, participants discussed several desired repository features, including: metadata control, data traceability, security, stable infrastructure, and data use restrictions. We present their desired repository features as a rubric for the research community to encourage repository utilization. Future directions for research are discussed.

URL : A focus groups study on data sharing and research data management

DOI : https://doi.org/10.1038/s41597-022-01428-w

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

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