Transparency in Authors’ Contributions and Responsibilities to Promote Integrity in Scientific Publication

McNutt, Marcia; Bradford, Monica; Drazen, Jeffrey M.; Hanson, Brooks; Howard, Bob; Jamieson, Kathleen Hall; Kiermer, Véronique; Magoulias, Michael; Marcus, Emilie; Pope, Barbara Kline; Schekman, Randy; Swaminathan, Sowmya; Stang, Peter J.; Verma, Inder M.

doi:10.1101/140228

Cited by 11 publications

(5 citation statements)

References 11 publications

(6 reference statements)

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“…This begins with author responsibility to properly manage their own data prior to submission. The Corresponding Author should have ultimate oversight responsibility to ensure this is done in a transparent, robust and effective way 16 . Researchers are also increasingly required by funders to submit data management plans.…”

Section: Update Information For Authorsmentioning

confidence: 99%

A data citation roadmap for scientific publishers

Cousijn

Kenall

Ganley

et al. 2017

Preprint

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This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP) [1], a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE program. The structure of the roadmap presented here follows the "life of a paper" workflow and includes the categories Pre-submission, Submission, Production, and Publication. The roadmap is intended to be publisher-agnostic so that all publishers can use this as a starting point when implementing JDDCP-compliant data citation. It can also act as a guide to authors -what to expect from publishers and how to enable their own data citations to gain maximum impact, as well as complying with what will become increasingly common funder mandates on data transparency.

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Section: Update Information For Authorsmentioning

confidence: 99%

A data citation roadmap for scientific publishers

Cousijn

Kenall

Ganley

et al. 2017

Preprint

View full text Add to dashboard Cite

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“…But even with disambiguated profiles, there remains the question of how to appropriately assign credit to co-authors for a given publication and related outcomes: a simple count of publications in which a researcher appears as an author (full counting) may be appropriate in some contexts but overestimates their contribution to co-authored publications (Sivertsen et al, 2019). Recent moves towards a contributor role taxonomy (McNutt et al, 2018) in research publications may be helpful for understanding task distribution in research teams but offer no implied weighting for crediting individual authors with a publication and subsequent citations or other types of impact. Instead, the state of the art remains in 'fractional' credit assignment (reviewed in Kim and Kim, 2015), by which a publication and any downstream impacts are attributed not in full to each author in the byline but on the basis of one of a variety of counting schemes that have been proposed (Waltman and van Eck, 2015).…”

Section: Taking the Measure Of Researchersmentioning

confidence: 99%

Meta-research and researcher evaluation

Plume

2024

Handbook of Meta-Research

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“…(Garijo and Poveda-Villalón, 2020)). Many other aspects of scientific communication have been approached with more formal representations, such as declaring authorship contributions with the Contributor Roles Taxonomy (McNutt et al, 2018) to mention just one of them.…”

Section: Scientific Knowledge Representationmentioning

confidence: 99%

Nanopublication-Based Semantic Publishing and Reviewing: A Field Study with Formalization Papers

Bucur¹,

Kuhn²,

Ceolin³

et al. 2022

Preprint

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With the rapidly increasing amount of scientific literature, it is getting continuously more difficult for researchers in different disciplines to keep up-to-date with the recent findings in their field of study. Processing scientific articles in an automated fashion has been proposed as a solution to this problem, but the accuracy of such processing remains very poor for extraction tasks beyond the most basic ones (like locating and identifying entities and simple classification based on predefined categories). Few approaches have tried to change how we publish scientific results in the first place, such as by making articles machine-interpretable by expressing them with formal semantics from the start. In the work presented here, we set out to demonstrate that we can formally publish high-level scientific claims in formal logic, and publish the results in a special issue of an existing journal. We use the concept and technology of nanopublications for this endeavor, and represent not just the submissions and final papers in this RDF-based format, but also the whole process in between, including reviews, responses, and decisions. We do this by performing a field study with what we call formalization papers, which contribute a novel formalization of a previously published claim. We received 15 submissions from 18 authors, who then went through the whole publication process leading to the publication of their contributions in the special issue. Our evaluation shows the technical and practical feasibility of our approach. The participating authors mostly showed high levels of interest and confidence, and mostly experienced the process as not very difficult, despite the technical nature of the current user interfaces. We believe that these results indicate that it is possible to publish scientific results from different fields with machineinterpretable semantics from the start, which in turn opens countless possibilities to radically improve in the future the effectiveness and efficiency of the scientific endeavor as a whole.

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Transparency in Authors’ Contributions and Responsibilities to Promote Integrity in Scientific Publication

Cited by 11 publications

References 11 publications

A data citation roadmap for scientific publishers

A data citation roadmap for scientific publishers

Meta-research and researcher evaluation

Nanopublication-Based Semantic Publishing and Reviewing: A Field Study with Formalization Papers

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