Data Mining and Knowledge Discovery
journal
Data Mining and Knowledge Discovery is a bimonthly peer-reviewed scientific journal focusing on data mining published by Springer Science+Business Media. It was started in 1996 and launched in 1997 by Usama Fayyad as founding Editor-in-Chief by Kluwer Academic Publishers (later becoming Springer). The first Editorial provides a summary of why it was started.
Academic status
Since its founding in 1997, this journal has become the most influential academic journal in the field. Each year, it currently publishes about 60 articles in six issues. It has one of the highest index ratings and is considered authoritative academically.
“Data Mining and Knowledge Discovery” enters the record as journal. Crown Archives preserves that source wording while asking what Data, Mining and Knowledge can confirm, complicate or overturn.
Why this record matters
“Data Mining and Knowledge Discovery” is worth following because a concise public description often conceals a longer documentary argument. Here, Data, Mining and Knowledge provides the most credible route into that argument.
Vocabulary and entity names are the principal evidence signals here, because they determine the precision of every later search. The source revision retrieved here is dated Jul 9, 2026. The linked authority identifier is Q5227191. 3 of 3 selected statements include explicit references; 1 carry qualifiers and 0 use preferred rank. The first chronological checks are 1996 and 1997.
The absence of detail may reflect summary conventions rather than a lack of surviving documentation. The lead is largely declarative, so disagreement and counter-evidence require a deliberate search beyond the opening account. Authority statements aid reconciliation but still require their own references, qualifiers and ranks to be checked.
How to read it
Use the entry as an orientation point, then follow its citations and revision history. Names, dates and institutional relationships should be checked against the original record.
- Subject orientation
- Search vocabulary
- Locating named sources
The closest primary source, responsible institution and strongest cited specialist reference.
Three-step research path
- Establish the record: confirm the title “Data Mining and Knowledge Discovery”, its source revision and the description used here.
- Expand the search: follow Data Mining and Knowledge Discovery primary sources, Data Mining and Knowledge Discovery archive and Data research across catalogues and specialist indexes.
- Test the account: compare the strongest cited source with the responsible institution’s current record and note any disagreement.
Questions for further research
- Which source most directly establishes the central claim about “Data Mining and Knowledge Discovery”?
- What terminology or title could unlock a more precise catalogue search?
- Which institution is responsible for the underlying evidence?
Search terms from this dossier
This entry incorporates text from “Data Mining and Knowledge Discovery” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.