PreprintToPaper dataset: connecting bioRxiv preprints with journal publications Some preprints get published, while others remain preprints without ever being formally published in a journal. The PreprintToPaper dataset is the first of its kind, as it attempts to automatically collect publication information from bioRxiv preprints and track whether submitted preprints have resulted in a publication. The dataset generated in this study was retrieved from the bioRxiv preprint server and the Crossref metadata API in July 2024. The dataset covers two time periods: the pre-pandemic period (2016–2018) and the COVID-19 pandemic period (2020–2022). The dataset contains detailed metadata about preprints and their published versions, including titles, authors, abstracts, institutions, submission and publication dates, licenses, and subject categories. The metadata was processed to facilitate analysis, for example, by standardizing date formats, normalizing author names, and selecting the first and last version of each preprint. The PreprintToPaper dataset offers diverse opportunities to study changes in titles, abstracts, and author composition over different stages of a preprint, starting from the initial submission through revision stages to the final published version. Main file provided: PreprintToPaper.csv — This is the main dataset containing all processed preprints from both time periods. Keywords BioRxiv, Crossref, preprints, publications Paper A paper describing this dataset is currently under preparation. Usage Data Collection Preprint metadata were retrieved via the bioRxiv API - api.biorxiv.org/details/[server]/[interval]/[cursor]/[format] Published paper metadata were retrieved via the Crossref API based on published DOI. api.crossref.org/works/[doi] As a result, 48,300 preprint records were obtained for the 2016–2018 period and 152,869 for the 2020–2022 period. Data Processing If both the initial and last versions of the preprint were available during the relevant period, both versions were retained. If only one version was available and it was the initial version, that version was retained. If only non-initial versions were available during the relevant period, the records were deleted. Unlinked publications in bioRxiv were identified by checking preprints. The preprints were identified by checking preprints against two criteria: title similarity and author similarity. Title similarity was measured using a matching score, and only cases with a score between 0.75 and 1 were considered. For the 19,090 rows that met this threshold, an additional author match score was calculated to more accurately identify unlinked publications. The dataset was categorized into 3 groups: published, preprint only and gray zone. See explanations below: Published: Preprints that were already linked on bioRxiv to a published article. Preprint only: Preprints that did not have any corresponding published version and could not be linked in bioRxiv. Gray zone: Preprints with potential matches based on title and author similarity, but without a confirmed publication DOI link. After data processing, in total, 33,687 preprints remained for the period 2016–2018, and 111,830 preprints for the period 2020–2022. Final Dataset The dataset includes 145,517 preprints, of which: 90,614 were linked to journal publications “Published”, 35,813 remain "Preprint Only", 19,090 are "Gray Zone". Summary Statistics Period Gray Zone Preprint Only Published Total Preprints 2016 359 1,019 3,343 4,721 2017 841 2,314 8,191 11,346 2018 1,121 4,115 12,943 18,179 2020 3,746 8,884 26,081 38,711 2021 5,292 8,987 22,539 36,818 2022 7,731 10,494 17,517 35,742 Total 19,090 35,813 90,614 145,517 Main Dataset Column Descriptions Column Name Description biorxiv_doi DOI for the bioRxiv preprint biorxiv_title_1st Preprint title - initial version biorxiv_title_last Preprint title – last version biorxiv_authors_1st Preprint authors – initial version biorxiv_authors_last Preprint authors – last version biorxiv_author_corresponding_1st Corresponding author – initial version biorxiv_author_corresponding_last Corresponding author - last version. biorxiv_author_corresponding_institution Affiliation of corresponding author biorxiv_submission_date_1st Submission date – initial version biorxiv_submission_date_last Submission date – last version custom_biorxivVersion_dateDifference Number of days between initial and last submission biorxiv_version_last Last preprint version number (e.g., 5 if 5 versions have been submitted) biorxiv_type Preprint type on bioRxiv (e.g., confirmatory, contradictory, new result) biorxiv_license Preprint license biorxiv_category Subject category assigned by bioRxiv (e.g., bioinformatics, genetics) biorxiv_jatsxml JATS XML structure (if available). This provides a link to the JATS XML file of the preprint. The file contains both metadata and full text of preprint. biorxiv_abstract_1st Abstract – initial version biorxiv_abstract_last Abstract – last version biorxiv_published_doi DOIs of published versions of preprints. The values come from two sources: (1) DOIs directly provided by bioRxiv for preprints with an official published link, and (2) DOIs additionally identified for preprints in the gray zone, where a publication was found but not directly linked in bioRxiv. custom_status Custom classification of the preprint status: Published, Preprint Only, or Gray Zone crossref_journal_name Journal name where the preprint was published (retrieved from Crossref) crossref_title Published paper title (listed in Crossref) crossref_authors Publish paper author list from Crossref crossref_publication_date Publication date (either online publication or issue date) crossref_publication_date_type Indicates whether the final date was from online publication or issue custom_submission&publication_dateDiff Days from preprint submission to publication author_count_diff Difference in the number of authors between the bioRxiv preprint and its published version. Positive = Positive values indicate more authors, negative = negative values indicate fewer. title_match_score Text similarity score (e.g., from SequenceMatcher) between the bioRxiv preprint title and the published article title. Only pairs with a score between 0.75 and 1.0 were considered potential matches. author_match_score Similarity score between preprint and published author lists, used to assess how closely the authors of a preprint match those of the corresponding published paper, particularly in gray zone cases. This score helps validate whether a gray zone publication link is correct. Additional Human-Annotated Subset In addition to the main dataset, a human-annotated subset is provided to support the evaluation of the automatic matching procedure. This subset includes preprints with custom_status = "gray zone" and a title match score of 0.75. The score is based on the similarity between titles and ranges from 0.75 to 1. The threshold of 0.75 was chosen based on checks performed on preprints with an official publication link in bioRxiv. In these checks, the similarity between preprint titles and the titles of their published versions was calculated, and in 91% of cases the score was ≥ 0.75. The results are presented in the file PreprintToPaper_GrayZone.csv. Matches in this subset were reviewed by two annotators using abstracts and, in some cases, full texts. This subset serves as an additional dataset for assessing the accuracy of the automatic matching procedure. · File name: PreprintToPaper_GrayZone.csv Column Descriptions Column Name Description year Preprint submission year biorxiv_doi bioRxiv preprint DOI suspected_published_doi Suspected DOI of the published article. Contains DOIs identified for gray zone preprints, where a potential published version was found but cannot be fully confirmed. author_match_score This score was used in the gray zone subset with 0.75 title match score to validate potential matches. Cases with a high author match score (close to 1) were in the majority confirmed as true matches by both annotators, while cases with a score of 0 were evaluated as non-matched. annotator1 / annotator2 Labels from two annotators (True, False, NA) Version-History Subset A separate version-history subset is provided to enable detailed analyses of how preprints evolve across multiple versions. This file contains all available in-period versions for preprints that have version 1 and at least one additional version within the study periods (2016–2018 and 2020–2022). Preprints with only a single version, or multi-version preprints for which version 1 is not present in our data, are not included in this subset. Each row corresponds to a single bioRxiv version. File name: PreprintToPaper_MultipleVersions.csv Column Descriptions Column Name Description biorxiv_doi DOI of the preprint. biorxiv_title Title of this version. biorxiv_authors Author list for this version. biorxiv_author_corresponding Corresponding author for this version. biorxiv_author_corresponding_institution Affiliation of the corresponding author for this version. biorxiv_submission_date Submission date of this version. biorxiv_version Version number on bioRxiv. biorxiv_type Preprint type on bioRxiv for this version. biorxiv_license License for this version. biorxiv_category Subject category assigned by bioRxiv. biorxiv_jatsxml JATS XML structure (if available) for this version. biorxiv_published_doi DOIs of published versions of preprints. This version-level subset complements the main dataset (which stores only the first and last version per preprint) and allows users to study, for example, incremental title changes or author-list updates across multiple bioRxiv versions.