Evidence map›Paper›PMID 38721398›Full record

ArticleBioinformatics advances2024

Perspectives on tracking data reuse across biodata resources.

Karen E Ross, Frederic B Bastian, Matt Buys, Charles E Cook, Peter D'Eustachio, Melissa Harrison, Henning Hermjakob, Donghui Li, Phillip Lord, Darren A Natale and 7 more

Abstract readEditorial
In one paragraph

Article in Bioinformatics advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Karen E RossProtein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, United States.ORCID https://orcid.org/0000-0003-4633-6055
Frederic B BastianEvolutionary Bioinformatics Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
Matt BuysDataCite, 30167 Hannover, Germany.
Charles E CookGlobal Biodata Coalition, Strasbourg 67080, France.
Peter D'EustachioDepartment of Biochemistry & Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10012, United States.
Melissa HarrisonLiterature Services, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.ORCID https://orcid.org/0000-0003-3523-4408
Henning HermjakobMolecular Systems, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.ORCID https://orcid.org/0000-0001-8479-0262
Donghui LiChan Zuckerberg Initiative, Redwood City, CA 94063, United States.
Phillip LordSchool of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, United Kingdom.
Darren A NataleProtein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, United States.
Bjoern PetersCenter for Vaccine Innovation, La Jolla Institute of Immunology, La Jolla, CA 92037, United States.
Paul W SternbergDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States.
Andrew I SuDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.ORCID https://orcid.org/0000-0002-9859-4104
Matthew ThakurData Services, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SA, United Kingdom.ORCID https://orcid.org/0000-0002-1325-1795
Paul D ThomasDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, United States.ORCID https://orcid.org/0000-0002-9074-3507
Alex BatemanMSCB, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.ORCID https://orcid.org/0000-0002-6982-4660
and the UniProt Consortium

Funding

UniProt - Text Mining and Large Language models to Enhance Functional Annotation in UniProt of Protein Variants Associated with Alzheimer's DiseaseU24HG007822 · NHGRI · GEORGETOWN UNIVERSITY · PI Alex Bateman, Alan James Bridge · 2018 to 2026
$53.0M
UniProt: A centralized protein sequence and function resourceU41HG007822 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI BATEMAN, ALEX · 2014 to 2017
$21.9M
Gene Ontology Consortium and KnowledgebaseU24HG012212 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHRISTOPHER J MUNGALL, PAUL Warren STERNBERG · 2022 to 2026
$11.6M
Reactome and the Gene Ontology: Digital pathway convergence for core data resourcesU24HG011851 · NHGRI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DEUSTACHIO, PETER G, MUNGALL, CHRISTOPHER J · 2021 to 2025
$3.6M
Protein Knowledge Networks and Semantic Computing for Disease DiscoveryR35GM141873 · NIGMS · UNIVERSITY OF DELAWARE · PI WU, CATHY H. · 2021 to 2025
$2.2M
NHGRI NIH HHS U24 HG007822NHGRI NIH HHS U24 HG011851NHGRI NIH HHS U24 HG012212NHGRI NIH HHS U41 HG007822NIGMS NIH HHS R35 GM141873
6 · The paper itself

Abstract

Motivation: Data reuse is a common and vital practice in molecular biology and enables the knowledge gathered over recent decades to drive discovery and innovation in the life sciences. Much of this knowledge has been collated into molecular biology databases, such as UniProtKB, and these resources derive enormous value from sharing data among themselves. However, quantifying and documenting this kind of data reuse remains a challenge. Results: The article reports on a one-day virtual workshop hosted by the UniProt Consortium in March 2023, attended by representatives from biodata resources, experts in data management, and NIH program managers. Workshop discussions focused on strategies for tracking data reuse, best practices for reusing data, and the challenges associated with data reuse and tracking. Surveys and discussions showed that data reuse is widespread, but critical information for reproducibility is sometimes lacking. Challenges include costs of tracking data reuse, tensions between tracking data and open sharing, restrictive licenses, and difficulties in tracking commercial data use. Recommendations that emerged from the discussion include: development of standardized formats for documenting data reuse, education about the obstacles posed by restrictive licenses, and continued recognition by funding agencies that data management is a critical activity that requires dedicated resources. Availability and implementation: Summaries of survey results are available at: https://docs.google.com/forms/d/1j-VU2ifEKb9C-sW6l3ATB79dgHdRk5v_lESv2hawnso/viewanalytics (survey of data providers) and https://docs.google.com/forms/d/18WbJFutUd7qiZoEzbOytFYXSfWFT61hVce0vjvIwIjk/viewanalytics (survey of users).

Identifiers

PMID38721398
PMCPMC11076920

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.