Open Scholarly Data @ SUB Göttingen
The Scholarly Communication Analytics team at the State and University Library in Göttingen maintains a publicly accessible Open Scholarly Data Warehouse, which is based on Google BigQuery.
The warehouse features monthly Crossref snapshots, as well as data from various other sources, including OpenAlex, Semantic Scholar and Unpaywall, and provides access to bibliometric data from the German Competence Network for Bibliometrics.
Google BigQuery is provided as part of the OCRE 2024 Framework, with support from the GWGD.
More info: https://subugoe.github.io/scholcomm_analytics/
Contact: Najko Jahn
cr_history
Description
Historical Crossref Snapshots. Only includes publications with type ‘journal-article’.
cr_instant
Description
This dataset contains the most recent Crossref Snapshot.
hoaddata
Description
Datasets used to compile hoaddata, an R package containing data about hybrid open access publishing https://subugoe.github.io/hoaddata/
oa2020
Description
Estimating global publishing output by leading commercial publishers using open metadata.
Work carried out for OA2020 WG on financial flows and future cost scenarios https://oa2020.org/working-groups/openalex
Description
This dataset contains the most recent OpenAlex Snapshot (before Walden).
openalex_walden
Description
This dataset contains the most recent OpenAlex-Walden Snapshot.
openbib
Description
This dataset contains the most recent OPENBIB snapshot.
For more information, see: https://zenodo.org/records/18429476resources
semantic_scholar
Description
This dataset contains a snapshot from Semantic Scholar.
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Data Source & License
This dataset contains information from the Semantic Scholar Open Research Corpus, provided by the Allen Institute for Artificial Intelligence (AI2) and made available under the Open Data Commons Attribution License (ODC-By) v1.0.
The ODC-By license governs the database rights only — that is, the structure, organisation, and compilation of the data. It does not cover the rights in the individual contents of the database, such as paper titles, abstracts, or full texts, which may be subject to separate copyright or license terms held by their respective authors, publishers, or other rights holders. Users are responsible for ensuring their use of any such content complies with the applicable terms.
For scientific publications making use of this data, please also cite:
Kyle Lo, Lucy Lu Wang, Mark Neumann, Rodney Kinney, and Daniel Weld. 2020. S2ORC: The Semantic Scholar Open Research Corpus. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4969–4983, Online. Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.447upw_history
Description
Historical Unpaywall Snapshots. Only includes records from 2008 onwards.
upw_instant
Description
This dataset contains the most recent Unpaywall Snapshot. Only records from 2008 onwards are included.