OpenAlex's reported average citation measure for a recent two-year publication window. It is not Clarivate's Journal Impact Factor or Scopus CiteScore; databases and calculation rules differ.
h-index
An h-index of 7 means at least 7 indexed papers have at least 7 citations each. It covers the source's indexed publication history and favors longer, larger records.
i10-index
Number of indexed papers with at least 10 citations. It is a count, not an average citation rate.
Papers / citations in OpenAlex
Indexed works and incoming citation links across the source's record. Coverage, missing metadata and indexing delays affect both totals.
Rank among tracked journals
Position within this site's tracked peer set and stated metric. It is not a global journal ranking, quartile or accreditation.
OpenAlex metrics below are not official Journal Impact Factor or CiteScore values. Any dated publisher-reported value is identified separately in the submission guide. Use the publisher's current information and the metric provider, checking the reference year. A small or new journal can have volatile citation averages; a missing value is not zero.
Before submitting, check the journal’s current aims, accepted article types, review procedure, data/code requirements, publication route and charges. Distinguish a submission fee from an open-access APC. Verify required database coverage by ISSN and year; this site’s OpenAlex metrics do not establish eligibility.
Data & Knowledge Engineering has a 2-year mean citedness of 5.21 and an h-index of 110 in OpenAlex, #24 of 28 tracked information systems journals by citedness.
In 2025 it published 108 papers, and its papers received 2,909 citations.
Data & Knowledge Engineering published 1 paper in the last 30 days (2026-10-07 to 2026-11-05), ranking #391 of 480 journals.
Leading institutions: Centro de Computação Gráfica (1), University of Minho (1) and Centro ALGORITMI (1).
Countries: Portugal (1).
45% of the papers Data & Knowledge Engineering published in 2023–2025 are open access in OpenAlex (hybrid 29%, bronze 4% and green 12%), #17 of 28 tracked information systems journals by open-access share.
From Nov 2023 to Oct 2026, Data & Knowledge Engineering published 283 papers (8 a month on average, by publication date in OpenAlex).
Its most frequent keywords over that period were “large language models” (35), “conceptual modeling” (21) and “knowledge graphs” (15).
Its most-cited paper of the period is “Artificial intelligence in digital twins—A systematic literature review” (2024-04-04), with 217 citations.
Papers per year and the citations the journal's papers received that year (OpenAlex)
Year
Papers
Citations received
2026 (so far)
77
2,057
2025
108
2,909
2024
84
2,763
2023
94
2,850
2022
85
2,650
2021
46
3,005
2020
30
2,905
2019
56
2,919
2018
72
3,006
2017
56
2,905
2016
30
3,092
2-year mean citedness is the recent-publication citation average reported by OpenAlex. It is a separate metric from Clarivate's Journal Impact Factor and Scopus CiteScore, with different coverage and rules; the h-index and i10-index cover the indexed publication history. The figures come from OpenAlex (CC0) and are read again monthly; the site's build date is not the metric's reference year.
Official Journal Impact Factor (Clarivate) and CiteScore (Scopus) values and current availability are not verified here. Consult the publisher and metric provider for the applicable reference year. Journal website →
Open-access status as OpenAlex reports it for each paper (diamond: published in an open-access journal that charges authors no fee; gold: published in an open-access journal; hybrid: open under a licence in a subscription journal; bronze: free to read on the publisher's site without an open licence; green: only a free copy in a repository; closed: no free copy found). Papers count by publication year; the share is of the papers whose status is known.
Pedro Guimarães, António Vieira, Maribel Yasmina Santos
Centro de Computação Gráfica; Centro ALGORITMI; University of Minho
Cite this page
Scholar4AI. (2026). Data & Knowledge Engineering. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/journals/data-knowledge-engineering
@misc{scholar4ai-journals-data-knowledge-engineering,
author = {{Scholar4AI}},
title = {Data & Knowledge Engineering},
year = {2026},
howpublished = {\url{https://scholar4ai.com/journals/data-knowledge-engineering}},
urldate = {2026-11-05},
note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).