OpenCitations Meta Provenance database

Compared to the previous version, this release includes provenance data related to citing and cited bibliographic resources added from the February 2026 version of Crossref (https://api.crossref.org/snapshots/monthly/2026/02/all.json.tar.gz) and the August 2025 version of JaLC (https://api.japanlinkcenter.org/). It also includes an alignment with OpenAlex identifiers (https://openalex.s3.amazonaws.com/browse.html). Moreover, this version introduces two new sources: OUTCITE (https://doi.org/10.5281/zenodo.18172742) and Matilda (https://matilda.science). This database contains the full provenance data for the OpenCitations Meta database, provided as a dump of the QLever index files. It includes a complete history of the creation and modification of every entity. The provenance information is modelled in RDF according to the OpenCitations Data Model (OCDM). Each change to an entity (creation, deletion, modification, or merge) is recorded in a "snapshot", which includes metadata about the agent responsible for the change, the primary source, and the timestamp. Snapshots are linked sequentially to provide a full version history of each entity. This dump describes the provenance of this OpenCitations Meta release, which contains:- 147,369,096 bibliographic entities- 422,366,470 authors, 3,673,399 editors, and 115,504,540 publishers (counted by their roles, without disambiguating individual entities)- 2,302,011 publication venues- A full-text index for textual searches. The data is provided as a multi-part 7zip archive. To extract it, please use the provided extraction scripts (`extract_archive.sh` for Linux/macOS and `extract_archive.bat` for Windows). The compressed archives total ~39G, using the 7-zip compression algorithm, and expand to ~192G when decompressed on an ext4 filesystem. Usage example (Linux/macOS):`bash extract_archive.sh oc_meta_prov_2026_06_27.7z.001 ./extracted_data`Usage example (Windows):`extract_archive.bat oc_meta_prov_2026_06_27.7z.001 .\extracted_data` For more information, please refer to the following paper: Arcangelo Massari, Fabio Mariani, Ivan Heibi, Silvio Peroni, David Shotton; OpenCitations Meta. Quantitative Science Studies 2024; 5 (1): 50–75. doi: https://doi.org/10.1162/qss_a_00292