“In an effort to support the reproducibility of published work, the Editors of the Journal of Chemical Information and Modeling (JCIM) have agreed on the following transparent policy for sharing scientific results as the best trade-off between reproducibility and, in some cases, the necessity to protect intellectual property and/or proprietary data….”
“Springer journals encourage posting of preprints of primary research manuscripts on preprint servers, authors’ or institutional websites, and open communications between researchers whether on community preprint servers or preprint commenting platforms. Preprints are defined as an author’s version of a research manuscript prior to formal peer review at a journal, which is deposited on a public server (as described in Preprints for the life sciences. Science 352, 899–901; 2016); preprints may be posted at any time during the peer review process. Posting of preprints is not considered prior publication and will not jeopardize consideration at Springer journals. Manuscripts posted on preprint servers will not be taken into account when determining the advance provided by a study under consideration at a Springer journal.
Our policy on posting, licensing, citation of preprints and communications with the media about preprints of primary research manuscripts is summarized below….”
“The Protein Data Bank (PDB) was established as the first open access repository for biological data, and the datasets it hosts have been invaluable to research in fundamental biology and the understanding of health and disease. Just this month, we witnessed the announcement of the AlphaFold2 results toward structure prediction, made possible thanks to the more than 170,000 freely accessible structures in the PDB which provided “training data” for the structure prediction software.
It was not always the case that such structural biology data were freely available, even upon journal publication. From the founding of the PDB in 1971 until the late 1980s, most journals did not require deposition of structures in a public database. A key moment was a petition, circulated in 1987 by a group of leading structural biologists, demanding that the data created be made openly available upon journal publication. This petition led to major journals adopting data deposition standards. In the early 1990s, the National Institute of General Medical Sciences (NIGMS) imposed similar requirements on all grantees.
The revolution in publishing made possible by preprints calls for a re-evaluation of data disclosure practices in structural biology. While journal review processes take weeks, months, or even years, preprints allow researchers to rapidly communicate their findings to the community. However, withholding access to PDB files that accompany preprints inhibits the progress towards scientific discovery which preprints can enable.
We pledge to publicly release our PDB files (and associated structure factor, restraint, and map files) with deposition of our preprints.
We encourage all structural biologists to also deposit raw data in appropriate resources (e.g. EMPIAR, proteindiffraction.org, https://data.sbgrid.org/, etc). …”
“Community abstracts are now mandatory for accepted submissions to JAMIA Open. Community abstracts support a key goal in dissemination of published work to the stakeholders that have the most to gain– the patients. I acknowledge the challenge for many of us who spend our time writing and communicating to research audiences to write Community Abstracts. However, for our field to have the most impact, we must convey our work to the greater community. Community understanding for our findings and innovations in leveraging informatics approaches to improve health and health care is a crucial first step toward building a foundation for reproducibility. That is, if a patient understands work presented in a publication, they should expect that it can be reproduced for themselves.
Reproducibility is on equal footing with rigor in terms of importance in the pursuit of knowledge. Many funding agencies now require explicit description for how proposed work will not only be rigorous but also reproducible. JAMIA Open has strongly encouraged the availability of any associated data (eg, through Dryad) to support reproducibility. Data that are made available through readily accessible, public repositories supports not only verification studies, but can also form the basis for new studies. Data sets can also be enhanced and curated to provide common “benchmark” datasets for algorithm evaluation.
JAMIA Open was established as a Level 1 Data Availability journal, meaning that authors were encouraged to share their data publicly. We are now shifting to be a Level 2 Data Availability journal, meaning that, in addition to sharing data publicly, each publication must include a Data Availability Statement. Of course, the release of data should only be done where ethically possible and in accordance to relevant laws. A description of the Oxford University Press Data Availability policies can be found here: https://academic.oup.com/journals/pages/authors/preparing_your_manuscript/research-data-policy….”
Abstract: The article describes a position statement and recommendations for actions that need to be taken to develop best practices for promoting scientific integrity through open science in health psychology endorsed at a Synergy Expert Group Meeting. Sixteen Synergy Meeting participants developed a set of recommendations for researchers, gatekeepers, and research end-users. The group process followed a nominal group technique and voting system to elicit and decide on the most relevant and topical issues. Seventeen priority areas were listed and voted on, 15 of them were recommended by the group. Specifically, the following priority actions for health psychology were endorsed: (1) for researchers: advancing when and how to make data open and accessible at various research stages and understanding researchers’ beliefs and attitudes regarding open data; (2) for educators: integrating open science in research curricula, e.g., through online open science training modules, promoting preregistration, transparent reporting, open data and applying open science as a learning tool; (3) for journal editors: providing an open science statement, and open data policies, including a minimal requirements submission checklist. Health psychology societies and journal editors should collaborate in order to develop a coordinated plan for research integrity and open science promotion across behavioural disciplines.
Abstract: Digital sharing of research data is becoming an important research integrity norm. Data sharing is promoted in different avenues, one being the scholarly publication process: journals serve as gatekeepers, recommending or mandating data sharing as a condition for publication. While there is now a sizeable corpus of research assessing the pervasiveness and efficacy of journal data sharing policies in various disciplines, available research is largely piecemeal and mitigates against meaningful comparisons across disciplines. A major contribution of the present research is that it makes direct across-discipline comparisons employing a common methodology. The paper opens with a discussion of the arguments aired in favour and against data sharing (with an emphasis on ethical issues, which stand behind these policies). The websites of 150 journals, drawn from 15 disciplines, were examined for information on data sharing. The results consolidate the notion of the primacy of biomedical sciences in the implementation of data sharing norms and the lagging implementation in the arts and humanities. More surprisingly, they attest to similar levels of norms adoption in the physical and social sciences. The results point to the overlooked status of the formal sciences, which demonstrate low levels of data sharing implementation. The study also examines the policies of the major journal publishers. The paper concludes with a presentation of the current preferences for different data sharing solutions in different fields, in specialized repositories, general repositories, or publishers’ hosting area.
“Even though The Journal of Social Psychology was one of the first psychology journals to adopt open science badges (J. E. Grahe, 2014), and the first to require Research Materials Transparency (J. Grahe, 2018), we have resisted requiring Data Transparency. The reasons for this have varied across the years, but most recently we paused for two reasons which I will present momentarily. However, our reasons were generally concerned that early adoption would drive away too many authors and we needed to wait. In the early spring of 2020, the editors once again discussed adopting Data Transparency as a requirement for publication, but again demurred. Though our other concerns were again discussed, the onset of the CV-19 pandemic was our primary caution. In short, we recognized that this decision will require a transition as authors grapple with a new reality of sharing their data as a condition of publication, and we were waiting until the time was right to implement the new rules. Well, the time has come, and this editorial is the announcement that Data Transparency will now be required for publication in The Journal of Social Psychology. Along with a short explanation of the timing, this editorial also describes what is required versus recommended in our new data sharing policy.”
“We live in the age of Big Data, and the current data boom is changing the way we do science. Data can be reanalyzed in new ways contributing to scientific information and knowledge. Accessible data also plays an essential role in encouraging responsible conduct. Researchers are increasingly sharing their data with the research community and Genome fully supports the goal of making research data available and accessible to everyone. Although data sharing is not mandatory for Genome, we do strongly encourage it….”
Abstract: Many scholarly journals have established their own data-related policies, which specify their enforcement of data sharing, the types of data to be submitted, and their procedures for making data available. However, except for the journal impact factor and the subject area, the factors associated with the overall strength of the data sharing policies of scholarly journals remain unknown. This study examines how factors, including impact factor, subject area, type of journal publisher, and geographical location of the publisher are related to the strength of the data sharing policy.
From each of the 178 categories of the Web of Science’s 2017 edition of Journal Citation Reports, the top journals in each quartile (Q1, Q2, Q3, and Q4) were selected in December 2018. Of the resulting 709 journals (5%), 700 in the fields of life, health, and physical sciences were selected for analysis. Four of the authors independently reviewed the results of the journal website searches, categorized the journals’ data sharing policies, and extracted the characteristics of individual journals. Univariable multinomial logistic regression analyses were initially conducted to determine whether there was a relationship between each factor and the strength of the data sharing policy. Based on the univariable analyses, a multivariable model was performed to further investigate the factors related to the presence and/or strength of the policy.
Of the 700 journals, 308 (44.0%) had no data sharing policy, 125 (17.9%) had a weak policy, and 267 (38.1%) had a strong policy (expecting or mandating data sharing). The impact factor quartile was positively associated with the strength of the data sharing policies. Physical science journals were less likely to have a strong policy relative to a weak policy than Life science journals (relative risk ratio [RRR], 0.36; 95% CI [0.17–0.78]). Life science journals had a greater probability of having a weak policy relative to no policy than health science journals (RRR, 2.73; 95% CI [1.05–7.14]). Commercial publishers were more likely to have a weak policy relative to no policy than non-commercial publishers (RRR, 7.87; 95% CI, [3.98–15.57]). Journals by publishers in Europe, including the majority of those located in the United Kingdom and the Netherlands, were more likely to have a strong data sharing policy than a weak policy (RRR, 2.99; 95% CI [1.85–4.81]).
These findings may account for the increase in commercial publishers’ engagement in data sharing and indicate that European national initiatives that encourage and mandate data sharing may influence the presence of a strong policy in the associated journals. Future research needs to explore the factors associated with varied degrees in the strength of a data sharing policy as well as more diverse characteristics of journals related to the policy strength.
“Researchers frequently need to know where and when they can share a copy of their submitted, accepted and/or published journal articles in order to: meet the requirements of a funder policy, share their research more widely through their institutional repository or a subject repository, or, decide where to publish. Most frequently, they look up the journal in question using the Sherpa RoMEO tool. However, many Canadian journals are not yet reflected in this leading international database, and for those that are, the information contained there can be old or incomplete.
CARL is therefore asking Canadian librarians, researchers, and journals to help us collect key information about these missing and incomplete journal entries to make it easier for researchers in Canada and beyond to find Canadian scholarly publication venues using this tool….”
To describe surgical journals’ position statements on data-sharing policies (primary objective) and to describe key features of their research transparency promotion.
Only “SURGICAL” journals with an impact factor higher than 2 (Web of Science) were eligible for the study. They were included, if there were explicit instructions for clinical trial publication in the official instructions for authors (OIA) or if they had published randomised controlled trial (RCT) between 1 January 2016 and 31 December 2018. The primary outcome was the existence of a data-sharing policy included in the instructions for authors. Data-sharing policies were grouped into 3 categories, inclusion of data-sharing policy mandatory, optional, or not available. Details on research transparency promotion were also collected, namely the existence of a “prospective registration of clinical trials requirement policy”, a conflict of interests (COIs) disclosure requirement, and a specific reference to reporting guidelines, such as CONSORT for RCT.
Among the 87 surgical journals identified, 82 were included in the study: 67 (82%) had explicit instructions for RCT and the remaining 15 (18%) had published at least one RCT. The median impact factor was 2.98 [IQR?=?2.48–3.77], and in 2016 and 2017, the journals published a median of 11.5 RCT [IQR?=?5–20.75].
The OIA of four journals (5%) stated that the inclusion of a data-sharing statement was mandatory, optional in 45% (n?=?37), and not included in 50% (n?=?41).
No association was found between journal characteristics and the existence of data-sharing policies (mandatory or optional). A “prospective registration of clinical trials requirement” was associated with International Committee of Medical Journal Editors (ICMJE) allusion or affiliation and higher impact factors. Journals with specific RCT instructions in their OIA and journals referenced on the ICMJE website more frequently mandated the use of CONSORT guidelines.
Research transparency promotion is still limited in surgical journals. Standardisation of journal requirements according to ICMJE guidelines could be a first step forward for research transparency promotion in surgery.
“Sharing relevant research data and findings: The Science Journals are signatories to the 2016 Statement on Data Sharing in Public Health Emergencies. The statement has been updated to address the 2019-nCoV outbreak. The update reaffirms the principles of rapid access to research data and papers relevant to the outbreak. Details can be found here: https://wellcome.ac.uk/press-release/sharing-research-data-and-findings-relevant-novel-coronavirus-ncov-outbreak.
Adapting our processes: In line with scientific recommendations, all editorial and operational staff of AAAS and the Science Journals are working from home during the COVID-19 pandemic. We could be working remotely for an extended period and we ask for your patience if this causes processing delays. We know that the outbreak is similarly impacting many of you – our authors, reviewers and readers. We all need to be flexible and patient during this difficult time. We thank you for your understanding. If you need help during the submission process, please email email@example.com. Please read our Editor’s Blog (https://blogs.sciencemag.org/editors-blog/) to learn more about our response to this continually evolving crisis….”
“Data Descriptors, Scientific Data’s primary article type, describe scientifically valuable datasets. These datasets must be made available to editors and referees at the time of submission, and must be shared with the scientific community as a condition of publication. Here, we provide information on the types of data that should be archived, guidance for authors on selecting a suitable repository for their data, and how to archive sensitive data.
Scientific Data’s data policies are compatible with the standardised research data policies set out by Springer Nature, and the requirements of the Data Policy Standardisation and Implementation Interest Group of the Research Data Alliance.
Please read on for our data deposition policies, and please contact us if you would like additional advice on how best to meet these requirements for your own data….”
“Accepted authors of Research articles are required to make their data accessible to the public. Data should always be submitted in raw data format, and should be submitted preferentially in publicly accessible resources maintained by for example EBI, EMBL, or NCBI data. Which data repository is used is up to the authors, however please visit http://www.elsevier.com/databaselinking for more information on depositing and linking your data with a supported data repository. For datatypes for which no such repositories exist, data should be made available through the supplementary information or the authors own website. If the data has been processed into e.g. pathways or models, then this should be made available also during the review process….”
“Under the pressure of a global health crisis, the argument for open access has sunk in. Following calls from the World Health Organization and government leaders, over 150 publishers, companies, and research institutions have agreed to temporarily make all content related to COVID-19 free to read, ensuring efforts to understand the virus can go forth undeterred….
Is this the catalyst that breaks up the bonds of an old publishing model once and for all? …”