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Data sharing policies of journals in life, health, and physical sciences indexed in Journal Citation Reports

Posté le 15 novembre 2020 par Hans Dillaerts

Authors : Jihyun Kim, Soon Kim, Hye-Min Cho, Jae Hwa Chang, Soo Young Kim

Background

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.

Methods

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.

Results

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]).

Conclusions

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.

URL : Data sharing policies of journals in life, health, and physical sciences indexed in Journal Citation Reports

DOI : https://doi.org/10.7717/peerj.9924

Research transparency promotion by surgical journals publishing randomised controlled trials: a survey

Posté le 7 novembre 2020 par Hans Dillaerts

Authors : Nicolas Lombard, A. Gasmi, L. Sulpice, K. Boudjema, Damien Bergeat

Objective

To describe surgical journals’ position statements on data-sharing policies (primary objective) and to describe key features of their research transparency promotion.

Methods

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.

Results

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.

Conclusion

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.

URL : Research transparency promotion by surgical journals publishing randomised controlled trials: a survey

DOI : https://doi.org/10.1186/s13063-020-04756-7

Towards FAIR protocols and workflows: the OpenPREDICT use case

Posté le 12 octobre 2020 par Hans Dillaerts

Authors : Remzi Celebi, Joao Rebelo Moreira, Ahmed A. Hassan, Sandeep Ayyar, Lars Ridder, Tobias Kuhn, Michel Dumontier

It is essential for the advancement of science that researchers share, reuse and reproduce each other’s workflows and protocols. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of research data, and emphasize the importance of making digital objects findable and reusable by others.

The question of how to apply these principles not just to data but also to the workflows and protocols that consume and produce them is still under debate and poses a number of challenges. In this paper we describe a two-fold approach of simultaneously applying the FAIR principles to scientific workflows as well as the involved data.

We apply and evaluate our approach on the case of the PREDICT workflow, a highly cited drug repurposing workflow. This includes FAIRification of the involved datasets, as well as applying semantic technologies to represent and store data about the detailed versions of the general protocol, of the concrete workflow instructions, and of their execution traces.

We propose a semantic model to address these specific requirements and was evaluated by answering competency questions. This semantic model consists of classes and relations from a number of existing ontologies, including Workflow4ever, PROV, EDAM, and BPMN.

This allowed us then to formulate and answer new kinds of competency questions. Our evaluation shows the high degree to which our FAIRified OpenPREDICT workflow now adheres to the FAIR principles and the practicality and usefulness of being able to answer our new competency questions.

URL : Towards FAIR protocols and workflows: the OpenPREDICT use case

DOI : https://doi.org/10.7717/peerj-cs.281

What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption

Posté le 10 octobre 2020 par Hans Dillaerts

Authors : Anneke Zuiderwijk, Rhythima Shinde, Wei Jeng

Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers’ drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking.

This study’s purpose is to systematically review the literature on individual researchers’ drivers and inhibitors for sharing and using open research data. This study systematically analyzed 32 open data studies (published between 2004 and 2019 inclusively) and elicited drivers plus inhibitors for both open research data sharing and use in eleven categories total that are: ‘the researcher’s background’, ‘requirements and formal obligations’, ‘personal drivers and intrinsic motivations’, ‘facilitating conditions’, ‘trust’, ‘expected performance’, ‘social influence and affiliation’, ‘effort’, ‘the researcher’s experience and skills’, ‘legislation and regulation’, and ‘data characteristics.’

This study extensively discusses these categories, along with argues how such categories and factors are connected using a thematic analysis. Also, this study discusses several opportunities for altogether applying, extending, using, and testing theories in open research data studies.

With such discussions, an overview of identified categories and factors can be further applied to examine both researchers’ drivers and inhibitors in different research disciplines, such as those with low rates of data sharing and use versus disciplines with high rates of data sharing plus use. What’s more, this study serves as a first vital step towards developing effective incentives for both open data sharing and use behavior.

URL : What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption

DOI : https://doi.org/10.1371/journal.pone.0239283

Research methodology and characteristics of journal articles with original data, preprint articles and registered clinical trial protocols about COVID-19

Posté le 3 septembre 2020 par Hans Dillaerts

Authors : Mahir Fidahic, Danijela Nujic, Renata Runjic, Marta Civljak, Zvjezdana Lovric Makaric, Livia Puljak

Background

The research community reacted rapidly to the emergence of COVID-19. We aimed to assess characteristics of journal articles, preprint articles, and registered trial protocols about COVID-19 and its causal agent SARS-CoV-2.

Methods

We analyzed characteristics of journal articles with original data indexed by March 19, 2020, in World Health Organization (WHO) COVID-19 collection, articles published on preprint servers medRxiv and bioRxiv by April 3, 2010.

Additionally, we assessed characteristics of clinical trials indexed in the WHO International Clinical Trials Registry Platform (WHO ICTRP) by April 7, 2020.

Results

Among the first 2118 articles on COVID-19 published in scholarly journals, 533 (25%) contained original data. The majority was published by authors from China (75%) and funded by Chinese sponsors (75%); a quarter was published in the Chinese language.

Among 312 articles that self-reported study design, the most frequent were retrospective studies (N = 88; 28%) and case reports (N = 86; 28%), analyzing patients’ characteristics (38%). Median Journal Impact Factor of journals where articles were published was 5.099.

Among 1088 analyzed preprint articles, the majority came from authors affiliated in China (51%) and were funded by sources in China (46%). Less than half reported study design; the majority were modeling studies (62%), and analyzed transmission/risk/prevalence (43%).

Of the 927 analyzed registered trials, the majority were interventional (58%). Half were already recruiting participants. The location for the conduct of the trial in the majority was China (N = 522; 63%).

The median number of planned participants was 140 (range: 1 to 15,000,000). Registered intervention trials used highly heterogeneous primary outcomes and tested highly heterogeneous interventions; the most frequently studied interventions were hydroxychloroquine (N = 39; 7.2%) and chloroquine (N = 16; 3%).

Conclusions

Early articles on COVID-19 were predominantly retrospective case reports and modeling studies. The diversity of outcomes used in intervention trial protocols indicates the urgent need for defining a core outcome set for COVID-19 research.

Chinese scholars had a head start in reporting about the new disease, but publishing articles in Chinese may limit their global reach. Mapping publications with original data can help finding gaps that will help us respond better to the new public health emergency.

URL : Research methodology and characteristics of journal articles with original data, preprint articles and registered clinical trial protocols about COVID-19

DOI : https://doi.org/10.1186/s12874-020-01047-2

FAIRness Literacy: The Achilles’ Heel of Applying FAIR Principles

Posté le 26 août 2020 par Hans Dillaerts

Authors : Romain David, Laurence Mabile, Alison Specht, Sarah Stryeck, Mogens Thomsen, Mohamed Yahia, Clement Jonquet, Laurent Dollé, Daniel Jacob, Daniele Bailo, Elena Bravo, Sophie Gachet, Hannah Gunderman, Jean-Eudes Hollebecq, Vassilios Ioannidis, Yvan Le Bras, Emilie Lerigoleur, Anne Cambon-Thomsen, The Research Data Alliance – SHAring Reward and Credit (SHARC) Interest Group

The SHARC Interest Group of the Research Data Alliance was established to improve research crediting and rewarding mechanisms for scientists who wish to organise their data (and material resources) for community sharing.

This requires that data are findable and accessible on the Web, and comply with shared standards making them interoperable and reusable in alignment with the FAIR principles. It takes considerable time, energy, expertise and motivation.

It is imperative to facilitate the processes to encourage scientists to share their data. To that aim, supporting FAIR principles compliance processes and increasing the human understanding of FAIRness criteria – i.e., promoting FAIRness literacy – and not only the machine-readability of the criteria, are critical steps in the data sharing process.

Appropriate human-understandable criteria must be the first identified in the FAIRness assessment processes and roadmap. This paper reports on the lessons learned from the RDA SHARC Interest Group on identifying the processes required to prepare FAIR implementation in various communities not specifically data skilled, and on the procedures and training that must be deployed and adapted to each practice and level of understanding.

These are essential milestones in developing adapted support and credit back mechanisms not yet in place.

URL : FAIRness Literacy: The Achilles’ Heel of Applying FAIR Principles

DOI : http://doi.org/10.5334/dsj-2020-032