Archives des mots-clés : data sharing

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

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Authors : Winfried Schröder, Stefan Nickel

Research Data Management (RDM) is regarded as an elementary component of empirical disciplines. Taking Landscape Ecology in Germany as an example the article demonstrates how to integrate RDM into the research design as a complement of the classic quality control and assurance in empirical research that has, so far, generally been limited to data production.

Sharing and reuse of empirical data by scientists as well as thorough peer reviews of knowledge produced by empirical research requires that the problem of the research in question, the operationalized definitions of the objects of investigation and their representative selection are documented and archived as well as the methods of data production including indicators for data quality and all data collected and produced.

On this basis, the extent to which this complemented design of research processes has already been realized is demonstrated by research projects of the Chair of Landscape Ecology at the University of Vechta, Germany.

This study is part of a joined research project on Research Data Management funded by the German Federal Ministry of Education and Research.

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

DOI : http://doi.org/10.5334/dsj-2020-026

Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences

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Authors : Rebecca Springer, Danielle Cooper

There is a growing perception that science can progress more quickly, more innovatively, and more rigorously when researchers share data with each other. However many scientists are not engaging in data sharing and remain skeptical of its relevance to their work.

As organizations and initiatives designed to promote STEM data sharing multiply – within, across, and outside academic institutions – there is a pressing need to decide strategically on the best ways to move forward. In this paper, we propose a new mechanism for conceptualizing and supporting STEM research data sharing.

Successful data sharing happens within data communities, formal or informal groups of scholars who share a certain type of data with each other, regardless of disciplinary boundaries. Drawing on the findings of four large-scale qualitative studies of research practices conducted by Ithaka S+R, as well as the scholarly literature, we identify what constitutes a data community and outline its most important features by studying three success stories, investigating the circumstances under which intensive data sharing is already happening.

We contend that stakeholders who wish to promote data sharing – librarians, information technologists, scholarly communications professionals, and research funders, to name a few – should work to identify and empower emergent data communities.

These are groups of scholars for whom a relatively straightforward technological intervention, usually the establishment of a data repository, could kickstart the growth of a more active data sharing culture. We conclude by offering recommendations for ways forward.

URL : Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences

DOI : https://doi.org/10.2218/ijdc.v15i1.695

Data-sharing recommendations in biomedical journals and randomised controlled trials: an audit of journals following the ICMJE recommendations

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Authors : Maximilian Siebert, Jeanne Fabiola Gaba, Laura Caquelin, Henri Gouraud, Alain Dupuy, David Moher, Florian Naudet

Objective

To explore the implementation of the International Committee of Medical Journal Editors (ICMJE) data-sharing policy which came into force on 1 July 2018 by ICMJE-member journals and by ICMJE-affiliated journals declaring they follow the ICMJE recommendations.

Design

A cross-sectional survey of data-sharing policies in 2018 on journal websites and in data-sharing statements in randomised controlled trials (RCTs).

Setting

ICMJE website; PubMed/Medline.

Eligibility criteria

ICMJE-member journals and 489 ICMJE-affiliated journals that published an RCT in 2018, had an accessible online website and were not considered as predatory journals according to Beall’s list. One hundred RCTs for member journals and 100 RCTs for affiliated journals with a data-sharing policy, submitted after 1 July 2018.

Main outcome measures

The primary outcome for the policies was the existence of a data-sharing policy (explicit data-sharing policy, no data-sharing policy, policy merely referring to ICMJE recommendations) as reported on the journal website, especially in the instructions for authors.

For RCTs, our primary outcome was the intention to share individual participant data set out in the data-sharing statement.

Results

Eight (out of 14; 57%) member journals had an explicit data-sharing policy on their website (three were more stringent than the ICMJE requirements, one was less demanding and four were compliant), five (35%) additional journals stated that they followed the ICMJE requirements, and one (8%) had no policy online. In RCTs published in these journals, there were data-sharing statements in 98 out of 100, with expressed intention to share individual patient data reaching 77 out of 100 (77%; 95% CI 67% to 85%).

One hundred and forty-five (out of 489) ICMJE-affiliated journals (30%; 26% to 34%) had an explicit data-sharing policy on their website (11 were more stringent than the ICMJE requirements, 85 were less demanding and 49 were compliant) and 276 (56%; 52% to 61%) merely referred to the ICMJE requirements.

In RCTs published in affiliated journals with an explicit data-sharing policy, data-sharing statements were rare (25%), and expressed intentions to share data were found in 22% (15% to 32%).

Conclusion

The implementation of ICMJE data-sharing requirements in online journal policies was suboptimal for ICMJE-member journals and poor for ICMJE-affiliated journals.

The implementation of the policy was good in member journals and of concern for affiliated journals. We suggest the conduct of continuous audits of medical journal data-sharing policies in the future.

URL : Data-sharing recommendations in biomedical journals and randomised controlled trials: an audit of journals following the ICMJE recommendations

DOI : http://dx.doi.org/10.1136/bmjopen-2020-038887

Toward Easy Deposit: Lowering the Barriers of Green Open Access with Data Integration and Automation

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Author : Hui Zhang

This article describes the design and development of an interoperable application that supports green open access with long-term sustainability and improved user experience of article deposit.

The lack of library resources and the unfriendly repository user interface are two significant barriers that hinder green open access.

Tasked to implement the open access mandate, librarians at an American research university developed a comprehensive system called Easy Deposit 2 to automate the support workflow of green open access.

Easy Deposit 2 is a web application that is able to harvest new publications, to source manuscripts on behalf of the library, and to facilitate self-archiving to a university’s institutional repository.

The article deposit rate increased from 7.40% to 25.60% with the launch of Easy Deposit 2. The results show that a computer system can implement routine tasks to support green open access with success.

Recent developments in digital repository provide new opportunities for innovation, such as Easy Deposit 2, in supporting open access.

Academic librarians are vital in promoting “openness” in scholarly communication, such as transparency and diversity in the sharing of publication data.

URL : Toward Easy Deposit: Lowering the Barriers of Green Open Access with Data Integration and Automation

DOI : https://doi.org/10.3390/publications8020028

Data Sharing in the Context of Health-Related Citizen Science

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Authors : Mary A. Majumder, Amy L. McGuire

As citizen science expands, questions arise regarding the applicability of norms and policies created in the context of conventional science. This article focuses on data sharing in the conduct of health-related citizen science, asking whether citizen scientists have obligations to share data and publish findings on par with the obligations of professional scientists.

We conclude that there are good reasons for supporting citizen scientists in sharing data and publishing findings, and we applaud recent efforts to facilitate data sharing.

At the same time, we believe it is problematic to treat data sharing and publication as ethical requirements for citizen scientists, especially where there is the potential for burden and harm without compensating benefit.

DOI : https://doi.org/10.1177/1073110520917044

SPI-Hub™: a gateway to scholarly publishing information

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Authors : Taneya Y. Koonce, Mallory N. Blasingame, Jerry Zhao, Annette M. Williams, Jing Su, Spencer J. DesAutels, Dario A. Giuse, John D. Clark, Zachary E. Fox, Nunzia Bettinsoli Giuse

Background

Advances in the health sciences rely on sharing research and data through publication. As information professionals are often asked to contribute their knowledge to assist clinicians and researchers in selecting journals for publication, the authors recognized an opportunity to build a decision support tool, SPI-Hub: Scholarly Publishing Information Hub™, to capture the team’s collective publishing industry knowledge, while carefully retaining the quality of service.

Case Presentation

SPI-Hub’s decision support functionality relies on a data framework that describes journal publication policies and practices through a newly designed metadata structure, the Knowledge Management Journal Record™.

Metadata fields are populated through a semi-automated process that uses custom programming to access content from multiple sources. Each record includes 25 metadata fields representing best publishing practices. Currently, the database includes more than 24,000 health sciences journal records.

To correctly capture the resources needed for both completion and future maintenance of the project, the team conducted an internal study to assess time requirements for completing records through different stages of automation.

Conclusions

The journal decision support tool, SPI-Hub, provides an opportunity to assess publication practices by compiling data from a variety of sources in a single location.

Automated and semi-automated approaches have effectively reduced the time needed for data collection.

Through a comprehensive knowledge management framework and the incorporation of multiple quality points specific to each journal, SPI-Hub provides prospective users with both recommendations for publication and holistic assessment of the trustworthiness of journals in which to publish research and acquire trusted knowledge.

URL : SPI-Hub™: a gateway to scholarly publishing information

Original location : http://jmla.pitt.edu/ojs/jmla/article/view/815

Did awarding badges increase data sharing in BMJ Open? A randomized controlled trial

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Authors : Anisa Rowhani-Farid, Adrian Aldcroft, Adrian G. Barnett

Sharing data and code are important components of reproducible research. Data sharing in research is widely discussed in the literature; however, there are no well-established evidence-based incentives that reward data sharing, nor randomized studies that demonstrate the effectiveness of data sharing policies at increasing data sharing.

A simple incentive, such as an Open Data Badge, might provide the change needed to increase data sharing in health and medical research. This study was a parallel group randomized controlled trial (protocol registration: doi:10.17605/OSF.IO/PXWZQ) with two groups, control and intervention, with 80 research articles published in BMJ Open per group, with a total of 160 research articles.

The intervention group received an email offer for an Open Data Badge if they shared their data along with their final publication and the control group received an email with no offer of a badge if they shared their data with their final publication.

The primary outcome was the data sharing rate. Badges did not noticeably motivate researchers who published in BMJ Open to share their data; the odds of awarding badges were nearly equal in the intervention and control groups (odds ratio = 0.9, 95% CI [0.1, 9.0]). Data sharing rates were low in both groups, with just two datasets shared in each of the intervention and control groups.

The global movement towards open science has made significant gains with the development of numerous data sharing policies and tools.

What remains to be established is an effective incentive that motivates researchers to take up such tools to share their data.

URL : Did awarding badges increase data sharing in BMJ Open? A randomized controlled trial

DOI : https://doi.org/10.1098/rsos.191818