The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Sharing Detailed Research Data Is Associated with Increased Citation Rate
Open accessAbstract
BACKGROUND: Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available. PRINCIPAL FINDINGS: We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression. SIGNIFICANCE: This correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.
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“Journal articles with accompanying data may be cited more frequently [248,249].”
From Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0 (2020) · cites this paper as [248]
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Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
Minimum information about a microarray experiment (MIAME)-toward standards for microarray data
Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C. A., Causton, H. C., et al. (2001) · Nature Genetics · doi:10.1038/ng1201-365 · Cited by 4,109
ONCOMINE: A Cancer Microarray Database and Integrated Data-Mining Platform
Rhodes, D. R., Yu, J., Sundaram, S. K., Deshpande, N., Varambally, R., Ghosh, D., Barrette, T. R., Pander, A., & Chinnaiyan, A. M. (2004) · Neoplasia · doi:10.1016/s1476-5586(04)80047-2 · Cited by 3,719
Why the impact factor of journals should not be used for evaluating research
Seglen, P. O. (1997) · BMJ · doi:10.1136/bmj.314.7079.497 · Cited by 2,447
Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)
McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/dji237 · Cited by 2,162
ArrayExpress--a public repository for microarray gene expression data at the EBI
Parkinson, H. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki056 · Cited by 1,077
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Eysenbach, G. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040157 · Cited by 829
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Antelman, K. (2004) · College & Research Libraries · doi:10.5860/crl.65.5.372 · Cited by 678
The Stanford Microarray Database
Sherlock, G. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.152 · Cited by 528
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Kansa, E. C. (2007) · Purdue e-Pubs (Purdue University System) · Cited by 1
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Reichmann, S. (2022) · doi:10.31235/osf.io/tbex2 · Cited by 2
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Huff, M., & Bongartz, E. C. (2022) · doi:10.31234/osf.io/9yhcz · Cited by 1
Balas, E. A. (2018) · doi:10.1002/9781119225898.ch18 · Cited by 1
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Reales, G., & Wallace, C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.27.509657 · Cited by 1
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(2016) · F1000Research Channels · doi:10.12688/f1000research.channels.103 · Cited by 1
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Mann, G. A., Small, N., Lee, K., Clarke, J., & Sheh, R. (2015) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2015.2452200
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Gilman, I., & Munoz, D. (2010) · CommonKnowledge Research Repository (Pacific University Oregon)
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Lange, M., Colmsee, C., Flemming, S., Chen, J., Klapperstück, M., & Scholz, U. (2010) · Nature Precedings · doi:10.1038/npre.2010.4935.1
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Metadata
- Authors
- Piwowar, H. A., Day, R. S., & Fridsma, D. B.
- Affiliations
- University of Pittsburgh (US)
- Corresponding author
- Piwowar, Heather A.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2007-03-21
- Volume
- 2
- Issue
- 3
- Pages
- e308
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC1817752
- OpenAlex
- W2046766973
- Cited by
- 881
- References
- 39
- Citations by year
- 2026: 17 · 2025: 25 · 2024: 35 · 2023: 49 · 2022: 71 · 2021: 71 · 2020: 73 · 2019: 40 · 2018: 68 · 2017: 54 · 2016: 61 · 2015: 64 · 2014: 47 · 2013: 74 · 2012: 40
- FWCI
- 50.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- D-Scholarship@Pitt (University of Pittsburgh) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- National Institutes of Health
- U.S. National Library of Medicine (T15LM007059)
- 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
- research data sharing, data availability, citation impact, public data, journal impact factor
- MeSH terms
- Clinical Trials as Topic, Cost-Benefit Analysis, Humans, Neoplasms, Periodicals as Topic, Publications, Regression Analysis, Internet, Oligonucleotide Array Sequence Analysis, Information Dissemination, Biomedical Research, Journal Impact Factor
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