Reproducible and reusable research: are journal data sharing policies meeting the mark?

Vasilevsky, Nicole; Minnier, Jessica; Haendel, Melissa; Champieux, Robin

doi:10.7717/peerj.3208

Cited by 137 publications

(125 citation statements)

References 25 publications

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“…For phylogenies, for example, it has been estimated that 60% of the data are not available to science [14]. Guidelines for sequence submission are standard for most journals, but such standards might not be true for other primary data; an analysis of the guidelines for authors of biomedical journals showed that only 12% of journals required general data sharing for publications [15]. Furthermore, the analysis presented here quantifies those studies that reported an accession number or link to sequence data, but it does not verify the quality of the attached metadata.…”

Section: Action To Ensure 'Open Sequencing Data'mentioning

confidence: 99%

Every fifth published metagenome is not available to science

et al. 2020

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Have you ever sought to use metagenomic DNA sequences reported in scientific publications? Were you successful? Here, we reveal that metagenomes from no fewer than 20% of the papers found in our literature search, published between 2016 and 2019, were not deposited in a repository or were simply inaccessible. The proportion of inaccessible data within the literature has been increasing year-on-year. Noncompliance with Open Data is best predicted by the scientific discipline of the journal. The number of citations, journal type (e.g., Open Access or subscription journals), and publisher are not good predictors of data accessibility. However, many publications in high-impact factor journals do display a higher likelihood of accessible metagenomic data sets. Twenty-first century science demands compliance with the ethical standard of data sharing of metagenomes and DNA sequence data more broadly. Data accessibility must become one of the routine and mandatory components of manuscript submissions-a requirement that should be applicable across the increasing number of disciplines using metagenomics. Compliance must be ensured and reinforced by funders, publishers, editors, reviewers, and, ultimately, the authors. Drivers of open dataScience, as an 'institution of organised criticism' [1], progresses through the act of building on communal knowledge by 'standing on the shoulders of giants'. Information sharing has been PLOS BIOLOGY PLOS Biology | https://doi.

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Section: Action To Ensure 'Open Sequencing Data'mentioning

confidence: 99%

Every fifth published metagenome is not available to science

et al. 2020

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“…Several studies explored compliance with journal data sharing policies [11][12][13][14][15]. For example, DAS in PLOS journals have been found to be significantly on the rise, after a mandated policy has been introduced, even if providing data in a repository remains a sharing method used only in a fraction of articles [16].…”

Section: Introductionmentioning

confidence: 99%

The citation advantage of linking publications to research data

et al. 2020

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Efforts to make research results open and reproducible are increasingly reflected by journal policies encouraging or mandating authors to provide data availability statements. As a consequence of this, there has been a strong uptake of data availability statements in recent literature. Nevertheless, it is still unclear what proportion of these statements actually contain well-formed links to data, for example via a URL or permanent identifier, and if there is an added value in providing such links. We consider 531, 889 journal articles published by PLOS and BMC, develop an automatic system for labelling their data availability statements according to four categories based on their content and the type of data availability they display, and finally 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. All our data and code are made available in order to reproduce and extend our results.

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“…Issues such as publication bias 49,50 and low statistical power 51,52 have been discussed in the behavioral and biomedical sciences for decades and data stakeholders including scholarly publishers and federal funding agencies have instituted a range of reproducibility-related policies stipulating how the data underlying published work should be managed and shared. For example, while mandates requiring authors to share the data underlying publications have been shown to increase the degree to which data is made available 53 , only a minority of biomedical journals have such requirements and even fewer provide specific guidance as to how to make data available and reusable 54 . Federal funding bodies generally exercise their RDM-related policies by requiring that a data management 8/14 Table 6.…”

Section: Discussionmentioning

confidence: 99%

Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers

Borghi

Gulick

2018

Preprint

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Neuroimaging methods such as magnetic resonance imaging (MRI) involve complex data collection and analysis protocols, which necessitate the establishment of good research data management (RDM). Despite efforts within the field to address issues related to rigor and reproducibility, information about the RDM-related practices and perceptions of neuroimaging researchers remains largely anecdotal. To inform such efforts, we conducted an online survey of active MRI researchers that covered a range of RDM-related topics. Survey questions addressed the type(s) of data collected, tools used for data storage, organization, and analysis, and the degree to which practices are defined and standardized within a research group. Our results demonstrate that neuroimaging data is acquired in multifarious forms, transformed and analyzed using a wide variety of software tools, and that RDM practices and perceptions vary considerably both within and between research groups, with trainees reporting less consistency than faculty. Ratings of the maturity of RDM practices from ad-hoc to refined were relatively high during the data collection and analysis phases of a project and significantly lower during the data sharing phase. Perceptions of emerging practices including open access publishing and preregistration were largely positive, but demonstrated little adoption into current practice.well-defined RDM practices in neuroimaging research. Even a relatively straightforward project involving MRI requires the management of data in a variety of forms from a variety of sources. In addition to the data collected using an MRI scanner, this may include sensitive medical information (e.g. pregnancy status, psychiatric and medical diagnoses), task-related behavioral data (e.g. response accuracy, reaction time), and questionnaire responses. Assessing, using, and replicating this work also requires access to documentation pertaining to participant characteristics, image acquisition and other scanning parameters, preprocessing and analysis procedures, as well as research materials including stimuli and custom code sets.However, the importance of RDM to neuroimaging research extends beyond the need to save and organize multifarious sets of materials. The BOLD (Blood Oxygen Level Dependant) signal, which underlies the majority of functional MRI studies, has a complex origin 11 , is potentially confounded by a number of physical, physiological, and behavioral variables 12 , and requires careful interpretation 13 . The process of analyzing MRI data is also highly flexible, iterative, and statistically challenging, with decisions made at an early stage having significant downstream effects 14 . Operating system type, software versions, and even hardware architecture have also been shown to significantly influence analytical results 15 . Thus, extensive documentation and justification of data acquisition and analysis parameters is essential. Unfortunately, despite the publication of best practice guidelines 11 , many articles describing the results of...

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Reproducible and reusable research: are journal data sharing policies meeting the mark?

Cited by 137 publications

References 25 publications

Every fifth published metagenome is not available to science

Every fifth published metagenome is not available to science

The citation advantage of linking publications to research data

Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers

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