CoChat
Sign Up
Cited by 336Research Data Management Practicesscientometrics and bibliometrics researchAcademic Publishing and Open Access

The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.

The citation advantage of linking publications to research data

Open access
Colavizza, Giovanni, Hrynaszkiewicz, Iain, Staden, Isla, Whitaker, Kirstie, McGillivray, Barbara·2020·PLOS ONE
DOI 10.1371/journal.pone.0230416PMC PMC7176083
Open this paper in CoChat — free accountOpen PDF

Abstract

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 become very common. In 2018 93.7% of 21,793 PLOS articles and 88.2% of 31,956 BMC articles had data availability statements. Data availability statements containing a link to data in a repository-rather than being available on request or included as supporting information files-are a fraction of the total. In 2017 and 2018, 20.8% of PLOS publications and 12.2% of BMC publications provided DAS containing a link to data in a repository. We also find an association between articles that include statements that link to data in a repository and up to 25.36% (± 1.07%) higher citation impact on average, using a citation prediction model. We discuss the potential implications of these results for authors (researchers) and journal publishers who make the effort of sharing their data in repositories. All our data and code are made available in order to reproduce and extend our results.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0230416

Cites

90 of 90 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 90 references

Research works printed but not linked: 3

  1. F Naudet, 2018, Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published in The BMJ and PLOS Medicine, BMJ, k400, 10.1136/bmj.k400 · DOI · Paper page
  2. PubMed. Open Access Collection; 2019. https://www.ncbi.nlm.nih.gov/pmc/tools/openftlist. Downloaded using the FTP service in February 2019.
  3. Archambault E, Beauchesne OH, Caruso J. Towards a multilingual, comprehensive and open scientific journal ontology. In: Proceedings of the 13th International Conference of the International Society for Scientometrics and Informetrics; 2011. p. 66–77.

Cited by

Sorted by citations

Items 201–300 of 336

Related

See all

Metadata

Authors
Colavizza, G., Hrynaszkiewicz, I., Staden, I., Whitaker, K., & McGillivray, B.
Affiliations
  • The Alan Turing Institute (GB)
  • Springer Nature (United Kingdom) (GB)
  • Queen Mary University of London (GB)
  • University of Cambridge (GB)
Corresponding author
McGillivray, Barbara
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2020-04-22
Volume
15
Issue
4
Pages
e0230416
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0230416
PMC
PMC7176083
OpenAlex
W2955244474
Cited by
335
References
90
Citations by year
2026: 27 · 2025: 48 · 2024: 47 · 2023: 58 · 2022: 71 · 2021: 51 · 2020: 25
FWCI
48.26
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • UvA-DARE (University of Amsterdam) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • arXiv (Cornell University)
  • Apollo (cc-by)
Funders
  • Engineering and Physical Sciences Research Council (EP/N510129/1)
  • Macmillan Education Ltd (RG92108)
Topics
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
  • Social Sciences › Library and Information Sciences › Academic Publishing and Open Access
Keywords
data availability statements, research data repositories, citation advantage, open science, reproducibility, PLOS, BMC, citation impact, data sharing
MeSH terms
Humans, Information Services, Publications, Research, Journal Impact Factor, Knowledge Discovery

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review