This paper empirically studies the effect of Open Access on journal CiteScores. We have found that the general effect is positive but not uniform across different types of journals. In particular, we investigate two types of heterogeneous treatment effect: (1) the differential treatment effect among journals grouped by academic field, publisher, and tier; and (2) differential treatment effects of Open Access as a function of propensity to be treated. The results are robust to a number of sensitivity checks and falsification tests. Our findings shed new light on Open Access effect on journals and can help stakeholders of journals in the decision of adopting the Open Access policy.
Transparency is essential for scientific progress. Access to underlying data and materials allows us to make progress through new discoveries and to better evaluate reported findings, which increases trust in science. However, there are challenges to changing norms of scientific practice. Culture change is a slow process because of inertia and the fear of unintended consequences.
One barrier to change that we encounter as we advocate to journals for more data sharing is an editor’s uncertainty about how their publisher will react to such a change. Will they help implement that policy? Will they discourage it because of uncertainty about how it might affect submission numbers or citation rates? With uncertainty, inaction seems to be easier.
“There are eight standards in the TOP guidelines; each moves scientific communication toward greater openness. These standards are modular, facilitating adoption in whole or in part. However, they also complement each other, in that commitment to one standard may facilitate adoption of others. Moreover, the guidelines are sensitive to barriers to openness by articulating, for example, a process for exceptions to sharing because of ethical issues, intellectual property concerns, or availability of necessary resources. The complete guidelines are available in the TOP information commons at http://cos.io/top, along with a list of signatories that numbered 86 journals and 26 organizations as of 15 June 2015. …
The journal article is central to the research communication process. Guidelines for authors define what aspects of the research process should be made available to the community to evaluate, critique, reuse, and extend. Scientists recognize the value of transparency, openness, and reproducibility. Improvement of journal policies can help those values become more evident in daily practice and ultimately improve the public trust in science, and science itself.”
“On this page you will find indicators on how the policies of journals and funding agencies favour open access, and the percentage of publications (green and gold) actually available through open access.
The indicators cover bibliometric data on publications, as well as data on funders’ and journals’ policies. Indicators and case studies will be updated over time.”
“Springer Nature was one of the founding members of ORCID, and since 2012 we have encouraged our authors to submit verified ORCID identifiers and we display them on published papers. This ensures authors get credit for their publications, and contributes to improving the transparency of scholarly communication by disambiguating name homonyms. To further support the uptake of ORCID, in 2017 Springer Nature engaged in a trial mandating ORCID identifiers for corresponding authors of primary research manuscripts at 46 journals across our portfolios.
The trial ran from April 27 for 6 months and the mandate was applied at different stages of the manuscript processing: 14 Nature-branded research journals required iDs at acceptance, while 10 BioMed Central (BMC) and 22 Springer journals did so at initial submission. Corresponding authors were able to share their ORCID identifier in the manuscript tracking system (via the ORCID API); without this step the submission would not proceed to the next stage….”
“The Science Journals support the Transparency and Openness Promotion (TOP) guidelines to raise the quality of research published in Science and to increase transparency regarding the evidence on which conclusions are based….All data used in the analysis must be available to any researcher for purposes of reproducing or extending the analysis. Data must be available in the paper, deposited in a community special-purpose repository, accessible via a general-purpose repository such as Dryad, or otherwise openly available….”
An open letter to the new editor-in-chief of Journal of Personality and Social Psychology: Attitudes and Social Cognition, urging the adoption of best practices for data sharing, reproducibility, and open science.
“A year ago the world’s leading medical-journal editors announced plans to require their authors to share with other scientists the data associated with their published articles about clinical trials. “I realistically think this will take several years” for the right environment to be in place, said Darren B. Taichman, secretary of the International Committee of Medical Journal Editors, which proposed the now-abandoned data-sharing requirement. The benefits of an open-data system are widely accepted by scientists. Sharing the data that underlie a journal article helps colleagues confirm the accuracy of the published finding, speed and expand their own research, and credit the originators, advocates have said. But the coalition of journal editors, also known as the ICMJE, said last week that a rash of complaints from scientists about the proposed requirement had led it to conclude that the research community still was not ready for the mandate….”
Open data is a vital pillar of open science and a key enabler for reproducibility, data reuse, and novel discoveries. Enforcement of open-data policies, however, largely relies on manual efforts, which invariably lag behind the increasingly automated generation of biological data. To address this problem, we developed a general approach to automatically identify datasets overdue for public release by applying text mining to identify dataset references in published articles and parse query results from repositories to determine if the datasets remain private. We demonstrate the effectiveness of this approach on 2 popular National Center for Biotechnology Information (NCBI) repositories: Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA). Our Wide-Open system identified a large number of overdue datasets, which spurred administrators to respond directly by releasing 400 datasets in one week.
“Advances in genetic sequencing and other technologies have led to an explosion of biological data, and decades of openness (both spontaneous and enforced) mean that scientists routinely deposit data in online repositories. But researchers are only human and may forget to tell a repository to release the data when a paper is published.
A new tool, developed by University of Washington and Microsoft researchers Maxim Grechkin, Hoifung Poon and Bill Howe, and described in a Community Page article publishing June 8 in the open access journal PLOS Biology, hopes to get around this problem and help advance open science by automatically detecting datasets that are overdue for publication…..”