BIP! DB: Impact Metrics for 106 Million Scientific Articles

September 2020 snapshot of citation data from OpenCitations, MAG, and Crossref. This dataset provides five distinct impact measures for over 106 million scientific articles, including citation counts and network centrality scores. It was produced by CERN and the European Commission and last updated in September 2023.

Use Cases

• Rank scientific articles based on total influence using the provided citation count.
• Assess a paper's initial momentum post-publication using the 3-year incubation citation count.
• Evaluate article importance within the citation network using the PageRank score.
• Measure current popularity or 'hype' of articles using the time-aware RAM and AttRank scores.

Strengths

• Contains 106,788,227 scientific articles, providing a large-scale corpus for analysis.
• Offers five distinct, algorithmically defined impact measures for each article.
• Built from a union of three major citation data sources: OpenCitations COCI, MAG, and Crossref.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is based on a snapshot from 2020; citations and scores for newer publications are not included.

Provenance

Source

CERN - European Organization for Nuclear Research and European Commission

Collection Method

Citation data gathered from OpenCitations’ COCI (Sep-2020), MAG (Aug-2020), and Crossref (Mar-2020) snapshots.

Time Range

Data snapshot from 2020.

Freshness

Last updated 2023-09-01 00:00:00; freshness should be verified.