Fig 1.
Data extraction and processing steps.
We first downloaded the PubMed open access collection (1) and created a database with all articles with a known identifier and which contained at least one reference (2; N = 1, 969, 175). Next we identified and disambiguated authors of these papers (3; S = 4, 253, 172) and calculated citations for each author and each publication from within the collection (4). We used these citation counts to calculate a within-collection H-index for each author. Our analysis only focuses on PLOS and BMC publications as these publishers introduced mandated DAS, so we filtered the database for these articles and extracted DAS from each publication (5). We annotated a training dataset by labelling each of these statements into one of four categories (6) and used those labels to train a natural language processing classifier (7). Using this classifier we then categorised the remaining DAS in the database (8). Finally, we exported this categorised dataset of M = 531, 889 publications to a csv file (9) and archived it (see Data and code availability section below).
Table 1.
Categories of DAS identified in our coding approach.
Table 2.
Classification report by DAS category.
Fig 2.
Data availability statements over time.
All the histograms above show the number of publications from specific subsets of the dataset and classify them into four categories: No DAS (0), Category 1 (data available on request), Category 2 (data contained within the article and supplementary materials), and Category 3 (a link to archived data in a public repository). The vertical solid line shows the date that the publisher introduced a mandated DAS policy. A dashed line indicates the date an encouraged policy was introduced. The groups of articles are as follows. A: all BMC articles, B: all PLOS articles, C: all BMC Series articles, D: PLOS One articles, E: PLOS articles not published in PLOS One, F: articles from the BMC Genomics journal (selected to illustrate a journal that had high uptake of an encouraged policy), G: articles from the Trials journal (published by BMC, selected to illustrate a journal that has a very high percentage of data that can only be made available by request to the authors), H: articles from the Parasites and Vectors journal (selected to illustrate a journal that has an even distribution of the three DAS categories). Articles are binned by publication year.
Table 3.
Summary of variables used in the regression models.
Table 4.
Descriptive statistics for (non-trasformed) model variables over the whole dataset under analysis.
Table 5.
Correlations among a set of variables.
The values on the top-right half of the table over the diagonal are Spearman’s correlation coefficients, the values on the bottom-left half of the table over the diagonal are Pearson’s correlation coefficients. All variables are transformed as in the description of the model.
Table 6.
OLS and robust LS estimates for the citation prediction model under discussion.
Coefficient standard errors are given in parentheses.