Category: Open Science

"Springer Nature and the Association of Universities in the Netherlands Partner to Explore How Open Research Can Accelerate Progress Towards the UN Sustainable Development Goals"

http://www.stm-publishing.com/springer-nature-and-the-association-of-universities-in-the-netherlands-partner-to-explore-how-open-research-can-accelerate-progress-towards-the-un-sustainable-development-goals/

An Analysis of Open Science Policies in Europe V4

SPARC Europe and the DCC have released An Analysis of Open Science Policies in Europe V4.

Here's an excerpt:

This document presents an updated review of Open Data and Open Science policies in Europe as of July 2019. It does not include Open Access to publications policy. This analysis goes more into depth on the types of policy in place in Europe, their processes of creation, and some of their specifics.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"medRxiv to PLOS: Direct Preprint Transfers"

PLOS has released "medRxiv to PLOS: Direct Preprint Transfers."

Here's an excerpt:

Authors with preprints on the new health sciences preprint server medRxiv now have the option to transfer their manuscripts for publication consideration at relevant PLOS journals in the topic area, PLOS Medicine, PLOS NTDs, or PLOS ONE. PLOS is excited to be among the first publishers to offer direct transfer service from the new server.

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"Open Science and Modified Funding Lotteries Can Impede the Natural Selection of Bad Science"

Paul E. Smaldino et al. have published "Open Science and Modified Funding Lotteries Can Impede the Natural Selection of Bad Science" in Royal Society Open Science.

Here's an excerpt:

Assessing scientists using exploitable metrics can lead to the degradation of research methods even without any strategic behaviour on the part of individuals, via 'the natural selection of bad science.' Institutional incentives to maximize metrics like publication quantity and impact drive this dynamic. Removing these incentives is necessary, but institutional change is slow. However, recent developments suggest possible solutions with more rapid onsets. These include what we call open science improvements, which can reduce publication bias and improve the efficacy of peer review. In addition, there have been increasing calls for funders to move away from prestige- or innovation-based approaches in favour of lotteries. We investigated whether such changes are likely to improve the reproducibility of science even in the presence of persistent incentives for publication quantity through computational modelling. We found that modified lotteries, which allocate funding randomly among proposals that pass a threshold for methodological rigour, effectively reduce the rate of false discoveries, particularly when paired with open science improvements that increase the publication of negative results and improve the quality of peer review. In the absence of funding that targets rigour, open science improvements can still reduce false discoveries in the published literature but are less likely to improve the overall culture of research practices that underlie those publications.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Academic Review Promotion and Tenure Documents Promote a View of Open Access That Is at Odds with the Wider Academic Community"

Juan Pablo Alperin, Esteban Morales and Erin McKiernan have published "Academic Review Promotion and Tenure Documents Promote a View of Open Access That Is at Odds with the Wider Academic Community" in the LSE Impact of Social Sciences Blog.

Here's an excerpt:

In a recent study, analysing documents related to the review, promotion, and tenure (RPT) process at a representative set of 129 universities from the United States and Canada, only 5% of institutions mentioned Open Access. Just as fascinating as this lack of interest and support for making research OA, however, were the misconceptions we found surrounding the term itself. For example one document cautioned faculty against "publishing in journals that are widely considered to be predatory open access journals". Others equated OA with materials that are "self-published, inadequately refereed, open-access writing."

Given that the documents that govern the RPT process embed these misconceptions and false associations, we wanted to know how faculty themselves thought about OA. Do faculty commonly associate OA with low-quality, non-refereed, predatory content?

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"Developing a Research Data Policy Framework for All Journals and Publishers"

Iain Hrynaszkiewicz et al. have self-archived "Developing a Research Data Policy Framework for All Journals and Publishers."

Here's an excerpt:

More journals and publishers—and funding agencies and institutions—are introducing research data policies. But as the prevalence of policies increases, there is potential to confuse researchers and support staff with numerous or conflicting policy requirements. We define and describe 14 features of journal research data policies and arrange these into a set of six standard policy types or tiers, which can be adopted by journals and publishers to promote data sharing in a way that encourages good practice and is appropriate for their audience's perceived needs. Policy features include coverage of topics such as data citation, data repositories, data availability statements, data standards and formats, and peer review of research data. These policy features and types have been created by reviewing the policies of multiple scholarly publishers, which collectively publish more than 10,000 journals, and through discussions and consensus building with multiple stakeholders in research data policy via the Data Policy Standardisation and Implementation Interest Group of the Research Data Alliance. Implementation guidelines for the standard research data policies for journals and publishers are also provided, along with template policy texts which can be implemented by journals in their Information for Authors and publishing workflows. We conclude with a call for collaboration across the scholarly publishing and wider research community to drive further implementation and adoption of consistent research data policies.

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"The Citation Advantage of Linking Publications to Research Data"

Giovanni Colavizza et al. have self-archived "The Citation Advantage of Linking Publications to Research Data."

Here's an excerpt:

We consider 531,889 journal articles published by PLOS and BMC which are part of the PubMed Open Access collection, categorize their data availability statements according to their content and analyze the citation advantage of different statement categories via regression. We find that, following mandated publisher policies, data availability statements have become common by now, yet statements containing a link to a repository are still just a fraction of the total. We also find that articles with these statements, in particular, can have up to 25.36% higher citation impact on average: an encouraging result for all publishers and authors who make the effort of sharing their data.

Research Data Curation Bibliography, Version 10 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"The Economic Impacts of Open Science: A Rapid Evidence Assessment"

Michael J. Fell has self-archived "The Economic Impacts of Open Science: A Rapid Evidence Assessment" in Preprints.

Here's an excerpt:

A common motivation for increasing open access to research findings and data is the potential to create economic benefits – but evidence is patchy and diverse. This study systematically reviewed the evidence on what kinds of economic impacts (positive and negative) open science can have, how these comes about, and how benefits could be maximized. Use of open science outputs often leaves no obvious trace, so most evidence of impacts is based on interviews, surveys, inference based on existing costs, and modelling approaches. There is indicative evidence that open access to findings/data can lead to savings in access costs, labour costs and transaction costs. There are examples of open science enabling new products, services, companies, research and collaborations. Modelling studies suggest higher returns to R&D if open access permits greater accessibility and efficiency of use of findings. Barriers include lack of skills capacity in search, interpretation and text mining, and lack of clarity around where benefits accrue. There are also contextual considerations around who benefits most from open science (e.g. sectors, small vs larger companies, types of dataset). Recommendations captured in the review include more research, monitoring and evaluation (including developing metrics), promoting benefits, capacity building and making outputs more audience-friendly.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap