Data Mining and Knowledge Discovery

Our screening does not flag Data Mining and Knowledge Discovery. That is not a guarantee of quality — it means the venue is not on Beall's archive (frozen since 2017) and does not match our name-pattern heuristic. It is listed in Scopus, Web of Science, PubMed, which is a positive signal.

Per our venue index, Data Mining and Knowledge Discovery appears in: Scopus, Web of Science, PubMed. Index membership changes over time — confirm on the index's own site before relying on it.

Papers in Data Mining and Knowledge Discovery are cited about 4.5 times each within two years of publication, and Scimago places it in Q1, with an h-index of 142. Those are the open equivalents: the Clarivate Journal Impact Factor is a proprietary metric we neither compute nor license, so we show the two-year citation rate and Scimago quartile instead — they answer the same question of how heavily the journal is cited. A citation rate is a property of a field as much as of a journal.

In the Scimago Journal Rank 2025 edition, Data Mining and Knowledge Discovery is Q1 in all 3 of its subject categories. By category: Computer Networks and Communications: Q1, #55 of 423; Information Systems: Q1, #67 of 434; Computer Science Applications: Q1, #155 of 875. Quartiles split the journals in a subject category into four equal groups by SJR, so Q1 is the most-cited quarter and Q4 the least; Data Mining and Knowledge Discovery is cited about 4.5 times per paper over two years, with an h-index of 142.

The Web of Science quartile comes from Clarivate's Journal Citation Reports (JCR), a proprietary product we neither license nor compute — so we cannot state a JCR quartile for Data Mining and Knowledge Discovery. The open equivalent is its Scimago quartile, Q1, derived from Scopus citation data. Because JCR ranks against Web of Science and Scimago against Scopus, the two can differ, so check Clarivate's site directly if you need the JCR quartile specifically.

Our index records its access status as "hybrid". Where this is derived from publisher-level signals rather than works-level data it is a heuristic, so confirm on the journal's own site — particularly if an article processing charge matters to you.

Submission to acceptance for Data Mining and Knowledge Discovery takes about 217 days (median) — Estimated from our library (n=22 papers). Treat it as indicative rather than a guarantee: editorial times vary by article type, reviewer availability and season, and a self-reported figure is the journal's own. We do not hold a peer-review acceptance rate for Data Mining and Knowledge Discovery.