Dataset Information

Is the open access citation advantage real? A systematic review of the citation of open access and subscription-based articles.

ABSTRACT:

Aims

Over the last two decades, the existence of an open access citation advantage (OACA)-increased citation of articles made available open access (OA)-has been the topic of much discussion. While there has been substantial research to address this question, findings have been contradictory and inconclusive. We conducted a systematic review to compare studies of citations to OA and non-OA articles.

Methods

A systematic search of 17 databases attempted to capture all relevant studies authored since 2001. The protocol was registered in Open Science Framework. We included studies with a direct comparison between OA and non-OA items and reported article-level citation as an outcome. Both randomized and non-randomized studies were included. No limitations were placed on study design, language, or publication type.

Results

A total of 5,744 items were retrieved. Ultimately, 134 items were identified for inclusion. 64 studies (47.8%) confirmed the existence of OACA, while 37 (27.6%) found that it did not exist, 32 (23.9%) found OACA only in subsets of their sample, and 1 study (0.8%) was inconclusive. Studies with a focus on multiple disciplines were significantly positively associated with finding that OACA exists in subsets, and are less associated with finding that OACA did not exist. In the critical appraisal of the included studies, 3 were found to have an overall low risk of bias. Of these, one found that an OACA existed, one found that it did not, and one found that an OACA occurred in subsets.

Conclusions

As seen through the large number of studies identified for this review, OACA is a topic of continuing interest. Quality and heterogeneity of the component studies pose challenges for generalization. The results suggest the need for reporting guidelines for bibliometrics studies.

SUBMITTER: Langham-Putrow A

PROVIDER: S-EPMC8221498 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Citation is one of the important metrics that are used in measuring the relevance and the impact of research publications. The potentials of citation analytics may be exploited to understand the gains of publishing scholarly peer-reviewed research outputs in either Open Access (OA) sources or Subscription-Based (SB) sources in the bid to increase citation impact. However, relevant data required for such comparative analysis must be freely accessible for evidence-based findings and conclusions. In this data article, citation scores (CiteScores) of 2542 OA sources and 15,040 SB sources indexed in Scopus from 2014 to 2016 were presented and analyzed based on a set of five inclusion criteria. A robust dataset, which contains the CiteScores of OA and SB publication sources included, is attached as supplementary material to this data article to facilitate further reuse. Descriptive statistics and frequency distributions of OA CiteScores and SB CiteScores are presented in tables. Boxplot representations and scatter plots are provided to show the statistical distributions of OA CiteScores and SB CiteScores across the three sub-categories (Book Series, Journal, and Trade Journal). Correlation coefficient and p-value matrices are made available within the data article. In addition, Probability Density Functions (PDFs) and Cumulative Distribution Functions (CDFs) of OA CiteScores and SB CiteScores are computed and the results are presented using tables and graphs. Furthermore, Analysis of Variance (ANOVA) and multiple comparison post-hoc tests are conducted to understand the statistical difference (and its significance, if any) in the citation impact of OA publication sources and SB publication source based on CiteScore. In the long run, the data provided in this article will help policy makers and researchers in Higher Education Institutions (HEIs) to identify the appropriate publication source type and category for dissemination of scholarly research findings with maximum citation impact.

Project description:Background. Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the "citation benefit". Furthermore, little is known about patterns in data reuse over time and across datasets. Method and Results. Here, we look at citation rates while controlling for many known citation predictors and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation benefit varied with date of dataset deposition: a citation benefit was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by year 4, and more than 150 data reuse papers had been published by year 5. Data reuse was distributed across a broad base of datasets: a very conservative estimate found that 20% of the datasets deposited between 2003 and 2007 had been reused at least once by third parties. Conclusion. After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation benefit are considered. We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003.

Project description:IntroductionAlong with the proliferation of Open Access (OA) publishing, the interest for comparing the scientific quality of studies published in OA journals versus subscription journals has also increased. With our study we aimed to compare the methodological quality and the quality of reporting of primary epidemiological studies and systematic reviews and meta-analyses published in OA and non-OA journals.MethodsIn order to identify the studies to appraise, we listed all OA and non-OA journals which published in 2013 at least one primary epidemiologic study (case-control or cohort study design), and at least one systematic review or meta-analysis in the field of oncology. For the appraisal, we picked up the first studies published in 2013 with case-control or cohort study design from OA journals (Group A; n = 12), and in the same time period from non-OA journals (Group B; n = 26); the first systematic reviews and meta-analyses published in 2013 from OA journals (Group C; n = 15), and in the same time period from non-OA journals (Group D; n = 32). We evaluated the methodological quality of studies by assessing the compliance of case-control and cohort studies to Newcastle and Ottawa Scale (NOS) scale, and the compliance of systematic reviews and meta-analyses to Assessment of Multiple Systematic Reviews (AMSTAR) scale. The quality of reporting was assessed considering the adherence of case-control and cohort studies to STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) checklist, and the adherence of systematic reviews and meta-analyses to Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) checklist.ResultsAmong case-control and cohort studies published in OA and non-OA journals, we did not observe significant differences in the median value of NOS score (Group A: 7 (IQR 7-8) versus Group B: 8 (7-9); p = 0.5) and in the adherence to STROBE checklist (Group A, 75% versus Group B, 80%; p = 0.1). The results did not change after adjustment for impact factor. The compliance with AMSTAR and adherence to PRISMA checklist were comparable between systematic reviews and meta-analyses published in OA and non-OA journals (Group C, 46.0% versus Group D, 55.0%; p = 0.06), (Group C, 72.0% versus Group D, 76.0%; p = 0.1), respectively).ConclusionThe epidemiological studies published in OA journals in the field of oncology approach the same methodological quality and quality of reporting as studies published in non-OA journals.