---
title: "Data & Knowledge Engineering: journal guide and metrics"
description: "Data & Knowledge Engineering: publisher, ISSN, official website, citation metrics explained and recent papers. Data & Knowledge Engineering is published by Elsevier BV and belongs to our Information Systems collection."
url: https://scholar4ai.com/journals/data-knowledge-engineering
markdown_url: https://scholar4ai.com/journals/data-knowledge-engineering.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Data & Knowledge Engineering: publisher, ISSN, official website, citation metrics explained and recent papers. Data & Knowledge Engineering is published by Elsevier BV and belongs to our Information Systems collection. (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# Data & Knowledge Engineering

- 0 papers in the last 7 days
- category: Information Systems
- publisher: Elsevier BV
- ISSN 0169-023X
- Journal website: http://www.elsevier.com/locate/datak
- ISSN portal: https://portal.issn.org/resource/ISSN/0169-023X
- OpenAlex: https://openalex.org/S136993123

Back to the ranking: https://scholar4ai.com/rankings/journals.md

Rankings of Information Systems: [Information Systems dashboard](https://scholar4ai.com/categories/information-systems.md) · [Methods and datasets in Information Systems](https://scholar4ai.com/research-patterns.md#information-systems) · [Information Systems journal rankings by citations](https://scholar4ai.com/rankings/journal-metrics/information-systems.md) · [Top information systems institutions, 2023–2025](https://scholar4ai.com/rankings/institutions-by-year/information-systems.md) · [Top funders of information systems research](https://scholar4ai.com/rankings/funders/information-systems.md) · [Companies in information systems research](https://scholar4ai.com/rankings/companies/information-systems.md) · [Open access in information systems journals](https://scholar4ai.com/rankings/open-access/information-systems.md) · [Top Information Systems conferences](https://scholar4ai.com/proceedings/categories/information-systems.md)

## Journal at a glance

Data & Knowledge Engineering is published by Elsevier BV and belongs to our Information Systems collection.

*Journal at a glance*

| Basic information | Details |
|---|---|
| Journal | Data & Knowledge Engineering |
| Publisher | Elsevier BV |
| Tracked ISSN | 0169-023X |
| Our collection | Information Systems |
| Official website | [Publisher's journal page](http://www.elsevier.com/locate/datak) |

Basic information source: https://openalex.org/S136993123

## What the metrics mean

*How to read journal metrics*

| Metric | What it means |
|---|---|
| 2-year mean citedness | 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.

OpenAlex metric documentation: https://help.openalex.org/data/common-attributes/

## Choosing this journal

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.

[Publisher instructions](http://www.elsevier.com/locate/datak)

## Key findings

- 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.

## Citation metrics

*Citation metrics (OpenAlex)*

| Metric | Value |
|---|---:|
| 2-year mean citedness | 5.21 |
| h-index | 110 |
| i10-index | 1,324 |
| Papers in OpenAlex | 2,701 |
| Citations in OpenAlex | 72,878 |
| Rank among tracked information systems journals | [#24 of 28](https://scholar4ai.com/rankings/journal-metrics/information-systems.md) |

*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: http://www.elsevier.com/locate/datak

## The last 36 months

*Papers by publication date, Nov 2023 to Oct 2026*

| Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---:|---:|---:|---:|
| 86 | 109 | 88 | 283 |

*Most frequent keywords, Nov 2023 to Oct 2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 35 |
| 2 | conceptual modeling | 21 |
| 3 | [knowledge graphs](https://scholar4ai.com/keywords/knowledge-graphs.md) | 15 |
| 4 | process mining | 12 |
| 5 | [BERT](https://scholar4ai.com/keywords/bert.md) | 7 |
| 6 | event logs | 7 |
| 7 | [explainable AI](https://scholar4ai.com/keywords/explainable-ai.md) | 7 |
| 8 | [graph neural networks](https://scholar4ai.com/keywords/graph-neural-networks.md) | 7 |
| 9 | knowledge representation | 7 |
| 10 | ontology (information science) | 7 |

*Most-cited papers published Nov 2023 to Oct 2026*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 217 | 7.0 | [Artificial intelligence in digital twins—A systematic literature review](https://doi.org/10.1016/j.datak.2024.102304) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-04-04 | Tim Kreuzer, Panagiotis Papapetrou, Jelena Zdravković |
| 2 | 84 | 2.5 | [Issues in inter-organizational data sharing: Findings from practice and research challenges](https://doi.org/10.1016/j.datak.2024.102280) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-01-09 | Ilka Jussen-Lengersdorf, Frederik Möller, Julia Schweihoff et al. |
| 3 | 64 | 2.1 | [Effective text classification using BERT, MTM LSTM, and DT](https://doi.org/10.1016/j.datak.2024.102306) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-04-21 | Saman Jamshidi, Mahin Mohammadi, Saeed Bagheri et al. |
| 4 | 54 | 1.8 | [Large language models: Expectations for semantics-driven systems engineering](https://doi.org/10.1016/j.datak.2024.102324) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-05-23 | Robert Andrei Buchmann, Johann Eder, Hans-Georg Fill et al. |
| 5 | 44 | 1.4 | [Leveraging an Isolation Forest to Anomaly Detection and Data Clustering](https://doi.org/10.1016/j.datak.2024.102302) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-03-28 | Véronne Yepmo, Grégory Smits, Marie‐Jeanne Lesot et al. |

## Most-cited since November 2016

*The journal's most-cited papers published since November 2016*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 217 | 7.0 | [Artificial intelligence in digital twins—A systematic literature review](https://doi.org/10.1016/j.datak.2024.102304) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-04-04 | Tim Kreuzer, Panagiotis Papapetrou, Jelena Zdravković |
| 2 | 84 | 2.5 | [Issues in inter-organizational data sharing: Findings from practice and research challenges](https://doi.org/10.1016/j.datak.2024.102280) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-01-09 | Ilka Jussen-Lengersdorf, Frederik Möller, Julia Schweihoff et al. |
| 3 | 64 | 2.1 | [Effective text classification using BERT, MTM LSTM, and DT](https://doi.org/10.1016/j.datak.2024.102306) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-04-21 | Saman Jamshidi, Mahin Mohammadi, Saeed Bagheri et al. |
| 4 | 54 | 1.8 | [Large language models: Expectations for semantics-driven systems engineering](https://doi.org/10.1016/j.datak.2024.102324) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-05-23 | Robert Andrei Buchmann, Johann Eder, Hans-Georg Fill et al. |
| 5 | 44 | 1.4 | [Leveraging an Isolation Forest to Anomaly Detection and Data Clustering](https://doi.org/10.1016/j.datak.2024.102302) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-03-28 | Véronne Yepmo, Grégory Smits, Marie‐Jeanne Lesot et al. |
| 6 | 44 | 1.6 | [Explanation, semantics, and ontology](https://doi.org/10.1016/j.datak.2024.102325) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-06-25 | Giancarlo Guizzardi, Nicola Guarino |
| 7 | 38 | 1.8 | [How well can a large language model explain business processes as perceived by users?](https://doi.org/10.1016/j.datak.2025.102416) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2025-02-15 | Dirk Fahland, Fabiana Fournier, Lior Limonad et al. |
| 8 | 36 | 1.2 | [To prompt or not to prompt: Navigating the use of Large Language Models for integrating and modeling heterogeneous data](https://doi.org/10.1016/j.datak.2024.102313) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-05-06 | Adel Remadi, Karim El Hage, Yasmina Hobeika et al. |
| 9 | 36 | 1.2 | [An extended TF-IDF method for improving keyword extraction in traditional corpus-based research: An example of a climate change corpus](https://doi.org/10.1016/j.datak.2024.102322) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-05-30 | Liang‐Ching Chen |
| 10 | 31 | 1.0 | [Managerial risk data analytics applications using grey influence analysis (GINA)](https://doi.org/10.1016/j.datak.2024.102312) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 2024-05-01 | R. Rajesh |

## Open access

*Papers per year by open-access status (OpenAlex)*

| Year | Papers | Open access | Diamond | Gold | Hybrid | Bronze | Green | Closed |
|---|---:|---:|---:|---:|---:|---:|---:|---:|
| 2017 | 56 | 20% | 0% | 0% | 2% | 4% | 14% | 80% |
| 2018 | 72 | 22% | 0% | 0% | 1% | 1% | 19% | 78% |
| 2019 | 56 | 29% | 0% | 0% | 4% | 14% | 11% | 71% |
| 2020 | 30 | 23% | 0% | 0% | 0% | 10% | 13% | 77% |
| 2021 | 46 | 50% | 0% | 0% | 24% | 13% | 13% | 50% |
| 2022 | 85 | 32% | 0% | 0% | 6% | 15% | 11% | 68% |
| 2023 | 94 | 44% | 0% | 0% | 24% | 3% | 16% | 56% |
| 2024 | 83 | 54% | 0% | 0% | 36% | 8% | 10% | 46% |
| 2025 | 102 | 39% | 0% | 0% | 28% | 0% | 11% | 61% |
| 2026 (so far) | 75 | 56% | 0% | 0% | 41% | 4% | 11% | 44% |

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.

*Papers, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-17 | [Evaluating Large Language Models in conceptual modeling: An experimental design](https://doi.org/10.1016/j.datak.2026.102657) | [Data & Knowledge Engineering](https://scholar4ai.com/journals/data-knowledge-engineering.md) | 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

```bibtex
@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}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).