When are researchers willing to share their data? – Impacts of values and uncertainty on open data in academia

Abstract:  Background

E-science technologies have significantly increased the availability of data. Research grant providers such as the European Union increasingly require open access publishing of research results and data. However, despite its significance to research, the adoption rate of open data technology remains low across all disciplines, especially in Europe where research has primarily focused on technical solutions (such as Zenodo or the Open Science Framework) or considered only parts of the issue.

Methods and findings

In this study, we emphasized the non-technical factors perceived value and uncertainty factors in the context of academia, which impact researchers’ acceptance of open data–the idea that researchers should not only publish their findings in the form of articles or reports, but also share the corresponding raw data sets. We present the results of a broad quantitative analysis including N = 995 researchers from 13 large to medium-sized universities in Germany. In order to test 11 hypotheses regarding researchers’ intentions to share their data, as well as detect any hierarchical or disciplinary differences, we employed a structured equation model (SEM) following the partial least squares (PLS) modeling approach.

Conclusions

Grounded in the value-based theory, this article proclaims that most individuals in academia embrace open data when the perceived advantages outweigh the disadvantages. Furthermore, uncertainty factors impact the perceived value (consisting of the perceived advantages and disadvantages) of sharing research data. We found that researchers’ assumptions about effort required during the data preparation process were diminished by awareness of e-science technologies (such as Zenodo or the Open Science Framework), which also increased their tendency to perceive personal benefits via data exchange. Uncertainty factors seem to influence the intention to share data. Effects differ between disciplines and hierarchical levels.

When are researchers willing to share their data? – Impacts of values and uncertainty on open data in academia

Abstract:  Background

E-science technologies have significantly increased the availability of data. Research grant providers such as the European Union increasingly require open access publishing of research results and data. However, despite its significance to research, the adoption rate of open data technology remains low across all disciplines, especially in Europe where research has primarily focused on technical solutions (such as Zenodo or the Open Science Framework) or considered only parts of the issue.

Methods and findings

In this study, we emphasized the non-technical factors perceived value and uncertainty factors in the context of academia, which impact researchers’ acceptance of open data–the idea that researchers should not only publish their findings in the form of articles or reports, but also share the corresponding raw data sets. We present the results of a broad quantitative analysis including N = 995 researchers from 13 large to medium-sized universities in Germany. In order to test 11 hypotheses regarding researchers’ intentions to share their data, as well as detect any hierarchical or disciplinary differences, we employed a structured equation model (SEM) following the partial least squares (PLS) modeling approach.

Conclusions

Grounded in the value-based theory, this article proclaims that most individuals in academia embrace open data when the perceived advantages outweigh the disadvantages. Furthermore, uncertainty factors impact the perceived value (consisting of the perceived advantages and disadvantages) of sharing research data. We found that researchers’ assumptions about effort required during the data preparation process were diminished by awareness of e-science technologies (such as Zenodo or the Open Science Framework), which also increased their tendency to perceive personal benefits via data exchange. Uncertainty factors seem to influence the intention to share data. Effects differ between disciplines and hierarchical levels.

Scientific Authors in a Changing World of Scholarly Communication: What Does the Future Hold?

Abstract:  Scholarly communication in science, technology and medicine has been organized around journal-based scientific publishing for the past 350 years. Scientific publishing has unique business models and includes stakeholders with conflicting interests – publishers, funders, libraries, and scholars who create, curate, and consume the literature. Massive growth and change in scholarly communication, coinciding with digitalization, have amplified stresses inherent in traditional scientific publishing as evidenced by overwhelmed editors and reviewers, increased retraction rates, emergence of pseudo-journals, strained library budgets, and debates about the metrics of academic recognition for scholarly achievements. Simultaneously, several open access models are gaining traction and online technologies offer opportunities to augment traditional tasks of scientific publishing, develop integrated discovery services, and establish global and equitable scholarly communication through crowdsourcing, software development, big data management and machine learning. These rapidly evolving developments raise financial, legal and ethical dilemmas that require solutions while successful strategies are difficult to predict. Key challenges and trends are reviewed from the authors’ perspective about how to engage the scholarly community in this multifaceted process.

 

Dutch research institutions and Elsevier initiate world’s first national Open Science partnership

“The Association of Universities in the Netherlands (VSNU), The Netherlands Federation of University Medical Centres (NFU), The Dutch Research Council (NWO) and Elsevier, a global leader in research publishing and information analytics, have formed a novel partnership that includes publishing and reading services as well as the joint development of new open science services for  disseminating and evaluating knowledge. The partnership runs until 31 December 2024….”

Which pockets pay APCs? · Peter Suber

“When scholars publish in open-access journals that levy article processing charges (APCs), how often do they pay the APCs with personal funds, as opposed to funds from their employers, funders, or other sources? Several studies have turned up data on the question. This is my attempt to summarize their results….” 

Observations From An Author & Librarian | Internet Archive Blogs

“She’s an author of crime fiction. A college librarian. A recently retired faculty member at a small liberal arts college in Minnesota. For more than 30 years, Barbara Fister has felt the opposing pull from her publishers and the call of open access; from the need for books to make money and the desire for her published work to live on into the next century. Plus, this author and librarian has authored five books now available in the National Emergency Library. …”

APCs in the Wild | Open research | Springer Nature

“The whitepaper which was published in April 2020, explores data from Springer Nature authors on the source of article processing charge (APC) funding, along with feedback from institutional interviews to facilitate a greater understanding of where funding for APCs originates and how these sources are being used. 

Accelerating the transition to OA will involve bringing together multiple different funding streams, as well as tackling complex questions regarding redistribution of existing funds. Developments in OA business models and infrastructure are improving the ability to monitor article OA status and spending, a step that is crucial to enabling institutions and research funders to make informed decisions about funding for Gold OA, in particular with regard to agreements with publishers. However, there are still many APCs ‘in the wild’, in other words payments that are harder to monitor and that institutions and funders may be unaware of. This report explores the scale of ‘wild’ funding streams that remain for the most part unmonitored but which could be harnessed to accelerate a transition to OA….”

APCs in the Wild | Open research | Springer Nature

“The whitepaper which was published in April 2020, explores data from Springer Nature authors on the source of article processing charge (APC) funding, along with feedback from institutional interviews to facilitate a greater understanding of where funding for APCs originates and how these sources are being used. 

Accelerating the transition to OA will involve bringing together multiple different funding streams, as well as tackling complex questions regarding redistribution of existing funds. Developments in OA business models and infrastructure are improving the ability to monitor article OA status and spending, a step that is crucial to enabling institutions and research funders to make informed decisions about funding for Gold OA, in particular with regard to agreements with publishers. However, there are still many APCs ‘in the wild’, in other words payments that are harder to monitor and that institutions and funders may be unaware of. This report explores the scale of ‘wild’ funding streams that remain for the most part unmonitored but which could be harnessed to accelerate a transition to OA….”

Next Steps Toward Using CRediT for Credit | NISO website

“Ensuring that researchers get credit for all the work they do, not just for the papers they write, is essential if we are ever to move beyond the current culture of “publish or perish.” Securing funding, managing data, writing software, and more are every bit as important to the success of a research project. But these roles are typically harder to identify and, therefore, tend to be overlooked when a researcher’s work is being evaluated, for example, when they are applying for promotion or tenure or seeking funding.

The CRediT (Contributor Roles Taxonomy) initiative aims to make it easier for researchers to get the credit they deserve for all their contributions, by identifying 14 different roles that can be assigned to one or more contributors to a research project. This information can then be included in the metadata for any research output — articles, books/book chapters, datasets, etc.

The CRediT taxonomy grew out of a Wellcome Trust/Harvard University workshop in 2012, which led to a pilot project to test it out with a group of science journal editors, the results of which were reported in Nature Communications. The 14 roles that have been defined are:

Conceptualization: formulation or evolution of overarching research goals and aims
Data curation: management activities to annotate, scrub data, and maintain research data for initial use and later re-use
Formal analysis: application of statistical, mathematical, computational, or other formal techniques to analyze or synthesize study data
Funding acquisition: getting financial support for the project leading to the publication
Investigation: conducting the research and investigation process, specifically performing the experiments, or data/evidence collection
Methodology: development or design of the methodology; creation of models
Project administration: management and coordination responsibility for the research activity, planning, and execution
Resources: providing study materials, reagents, materials, patients, laboratory samples, animals, instrumentation, computing resources, or other analysis tools
Software: programming, software development; designing computer programs; implementation of the computer code and supporting algorithms; testing of existing code components
Supervision: oversight and leadership responsibility for the research activity planning and execution, including mentorship external to the core team
Validation: verification, whether as a part of the activity or separate, of the overall replication/reproducibility of results/experiments and other research outputs
Visualization: preparation, creation, and/or presentation of the published work, specifically visualization/data presentation
Writing – original draft: preparation, creation, and/or presentation of the published work, specifically writing the initial draft (including substantive translation)
Writing – review and editing: reparation, creation, and/or presentation of the published work by those from the original research group, specifically critical review, commentary or revision, including pre- or post-publication stages …”

Journal data policies: Exploring how the understanding of editors and authors corresponds to the policies themselves

Abstract:  Despite the increase in the number of journals issuing data policies requiring authors to make data underlying reporting findings publicly available, authors do not always do so, and when they do, the data do not always meet standards of quality that allow others to verify or extend published results. This phenomenon suggests the need to consider the effectiveness of journal data policies to present and articulate transparency requirements, and how well they facilitate (or hinder) authors’ ability to produce and provide access to data, code, and associated materials that meet quality standards for computational reproducibility. This article describes the results of a research study that examined the ability of journal-based data policies to: 1) effectively communicate transparency requirements to authors, and 2) enable authors to successfully meet policy requirements. To do this, we conducted a mixed-methods study that examined individual data policies alongside editors’ and authors’ interpretation of policy requirements to answer the following research questions. Survey responses from authors and editors along with results from a content analysis of data policies found discrepancies among editors’ assertion of data policy requirements, authors’ understanding of policy requirements, and the requirements stated in the policy language as written. We offer explanations for these discrepancies and offer recommendations for improving authors’ understanding of policies and increasing the likelihood of policy compliance.