Cited by 66Scientific Computing and Data ManagementResearch Data Management PracticesDistributed and Parallel Computing Systems

A systematic review of provenance systems

Open access
Pérez, Beatriz, Rubio, Julio, Sáenz-Adán, Carlos·2018·Knowledge and Information Systems

Integrity signals

Registry

Crossref · 10.1007/s10115-018-1164-3

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Pérez, B., Rubio, J., & Sáenz-Adán, C.
Affiliations
Universidad de La Rioja (ES)
Corresponding author
Pérez, Beatriz
Venue
Knowledge and Information Systems
Published
2018-02-17
Volume
57
Issue
3
Pages
495-543
ISSN
  • 0219-1377 (ISSN-L)
  • 0219-3116
OpenAlex
W2789202269
Cited by
66
References
3
Citations by year
2026: 7 · 2025: 9 · 2024: 9 · 2023: 11 · 2022: 9 · 2021: 7 · 2020: 7 · 2019: 4 · 2018: 3
FWCI
1.79
Type
journal article
Language
en
Locations
  • Knowledge and Information Systems (publishedVersion)
  • RIUR (Universidad de La Rioja) (submittedVersion, other-oa)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
Keywords
data provenance, provenance capture, provenance management, provenance storage, reproducibility, data quality, system comparison

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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