ArticlePloS one2020
Journal data policies: Exploring how the understanding of editors and authors corresponds to the policies themselves.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Self-reported availability of research data in American Psychological Association journal articles: a cross-sectional investigation.Research integrity and peer review · 2026Article
- From policy to practice: progress towards data- and code-sharing in ecology and evolution.Proceedings. Biological sciences · 2025Article
- FAIR data for optical tweezers experiments.Biophysical journal · 2025Review
- The reliability of replications: a study in computational reproductions.Royal Society open science · 2025Article
- Article
- A guide for social science journal editors on easing into open science.Research integrity and peer review · 2024Article
- Exchanging words: Engaging the challenges of sharing qualitative research data.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Reply to: Recognizing and marshalling the pre-publication error correction potential of open data for more reproducible science.Nature ecology & evolution · 2023Article
- How often do cancer researchers make their data and code available and what factors are associated with sharing?BMC medicine · 2022Article
- Promoting data quality and reuse in archaeology through collaborative identifier practices.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution.Proceedings. Biological sciences · 2022Article
- Guidance for ensuring fair and ethical broad consent for future use. A scoping review protocol.F1000Research · 2021Article
- CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility.F1000Research · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the increase in the number of journals issuing data policies requiring authors to make data underlying reporting findings publicly available, authors do not always do so, and when they do, the data do not always meet standards of quality that allow others to verify or extend published results. This phenomenon suggests the need to consider the effectiveness of journal data policies to present and articulate transparency requirements, and how well they facilitate (or hinder) authors' ability to produce and provide access to data, code, and associated materials that meet quality standards for computational reproducibility. This article describes the results of a research study that examined the ability of journal-based data policies to: 1) effectively communicate transparency requirements to authors, and 2) enable authors to successfully meet policy requirements. To do this, we conducted a mixed-methods study that examined individual data policies alongside editors' and authors' interpretation of policy requirements to answer the following research questions. Survey responses from authors and editors along with results from a content analysis of data policies found discrepancies among editors' assertion of data policy requirements, authors' understanding of policy requirements, and the requirements stated in the policy language as written. We offer explanations for these discrepancies and offer recommendations for improving authors' understanding of policies and increasing the likelihood of policy compliance.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.