ArticlePLoS computational biology2022
Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 20 citations in OpenAlex.
- Integrative Bioinformatics Approaches in Environmental Biotechnology: A Review.TheScientificWorldJournal · 2026Review
- Transparency of medical artificial intelligence systems.Nature reviews bioengineering · 2026Article
- Eleven quick tips to unlock the power of in vivo data science.PLoS computational biology · 2025Article
- Eleven quick tips for properly handling tabular data.PLoS computational biology · 2024Article
- Current best practices and future opportunities for reproducible findings using large-scale neuroimaging in psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Diversity and inclusion: A hidden additional benefit of Open Data.PLOS digital health · 2024Article
- Ethical considerations in utilizing artificial intelligence for analyzing the NHGRI's History of Genomics and Human Genome Project archives.Journal of escience librarianship · 2024Article
- Ten simple rules for humane data science.PLoS computational biology · 2023Article
- Ten simple rules for managing laboratory information.PLoS computational biology · 2023Article
- COLLAGENE enables privacy-aware federated and collaborative genomic data analysis.Genome biology · 2023Article
- Ten simple rules for organizations to support research data sharing.PLoS computational biology · 2023Article
- Bridging the gap: A library-based collaboration to enhance data skills for clinical researchers.Learning health systems · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The National Institutes of Health (NIH) Policy for Data Management and Sharing (DMS Policy) recognizes the NIH's role as a key steward of United States biomedical research and information and seeks to enhance that stewardship through systematic recommendations for the preservation and sharing of research data generated by funded projects. The policy is effective as of January 2023. The recommendations include a requirement for the submission of a Data Management and Sharing Plan (DMSP) with funding applications, and while no strict template was provided, the NIH has released supplemental draft guidance on elements to consider when developing a plan. This article provides 10 key recommendations for creating a DMSP that is both maximally compliant and effective.
Indexed as
Identifiers
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.