[CfP] 7th Workshop & Challenge on KG Construction @ ESWC2026

Seventh International Workshop & Challenge on Knowledge Graph Construction
(#KGCW2026) in conjunction with ESWC2026 [https://2026.eswc-conferences.org/]
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Workshop website: https://w3id.org/kg-construct/workshop/2026
Workshop date: 10th or 11th May 2026
Paper Submission:

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Abstracts (optional but recommended): 17th February 2026
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Full papers: 3rd of March 2026 (AoE time)

Challenge (https://w3id.org/kg-construct/workshop/2026/challenge.html):

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Interest for participation: February 28th, 2026 AoE. To participate is mandatory to fill out this form https://forms.gle/smzqTe67HBemEM3t6

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KGCW is a full-day workshop on Knowledge Graph construction co-located with the Extended Semantic Web Conference 2026 (ESWC2026)<https://2026.eswc-conferences.org/>. KGCW focuses this time on systematically assessing other aspects of KG generation beyond performance. For example, usability, usefulness, pipeline architecture coverage (of techniques, languages, and extensions), and the tradeoffs between various metrics and techniques in production settings. The focus on these aspects and their assessment enables the workshop to collect contributions from a wide range of topics, such as the role of generative LLMs in (declarative) KG Generation, automation and planning of KG processes, and the role of human stakeholders in KG processes. The workshop provides a venue for scientific discourse, systematic analysis, and rigorous evaluation of languages, techniques, and tools. We also welcome contributions about the practical and applied experiences and lessons learned from constructing knowledge graphs from academia and industry. The workshop complements and aligns with the activities of the W3C CG on KG construction<https://www.w3.org/community/kg-construct/>.

Topics of interest
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Automatization of knowledge graph construction from (semi)structured data:
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Semantic data labeling methods for declarative KG construction approaches
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(Semi-)automated mappings generation
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Explainable automated knowledge graph generation
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LLM-based approaches for automation of KG construction
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Mapping-based Knowledge Graph Construction
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Mapping languages for constructing Knowledge Graphs from legacy datasets
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End-User Interfaces (UI) for (collaborative) editing and visualizing Knowledge Graph building rules, and management platforms in general
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Approaches and techniques on
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Collaborative mappings generation
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Exploiting mappings for query answering
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Tools for Knowledge Graph Construction
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Architectures for Knowledge Graph construction systems
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(Sustainable) Workflows for Knowledge Graph construction & publishing
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Methods and Techniques for Knowledge Graph Construction
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Seamless (distributed) integration/interlinking of heterogeneous data
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Dynamic discovery and retrieval of data for KG construction
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Quality, Provenance, privacy, and trustworthiness of KG construction
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Knowledge Graph construction and publishing of streaming data
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Benchmarks for Knowledge Graphs construction and publishing
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Lessons learnt, In Use and Experience
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Experience, lessons learned, and best practices for generating and publishing
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Negative results and in-use/applied descriptions


Submission guidelines
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Share your contribution on the OpenReview platform<https://openreview.net/group?id=eswc-conferences.org/ESWC/2026/Workshop/KGCW> before the deadline. The accepted contributions will be published in the workshop proceedings. Each accepted paper must be presented by one of the authors at the workshop onsite.

Contributions for the challenge only require an abstract to be submitted through the OpenReview platform<https://openreview.net/group?id=eswc-conferences.org/ESWC/2026/Workshop/KGCW>. The results must be submitted and presented at the workshop. A report can be submitted after the workshop, which will appear in the workshop proceedings.

Contributions
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Full (12-15 pages) or short (5-8 pages) research papers, in general, or related to:
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Addressing issues identified by the W3C CG on KG construction
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Providing solutions for alignments between mapping languages
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Providing innovative and reproducible workflows for knowledge graph construction
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Automatization of KG construction
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New techniques and approaches for the new RML version.
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In Use and Experience papers (12-15 pages), as well as demo papers (4-6 pages)
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Challenge papers (6-8 pages)
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Position and Vision papers (4-6 pages)
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Abstracts of journal papers that are relevant to the aforementioned topics (2-4 pages)

Challenge
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Building on the growing adoption of knowledge graph construction in academia and industry, this year’s challenge spans three complementary dimensions:

  1.
Performance, benchmarking execution time, and resource efficiency (CPU/memory) for KG construction pipelines;
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Conformance, testing engine compliance with the latest RML specification and modules through an extensive suite of test cases; and
  3.
Mapping Methodology, encouraging novel and innovative approaches for defining and executing mappings, whether by extending RML and its ecosystem or by proposing entirely new mapping paradigms.

Participants will be evaluated on their ability to construct correct RDF graphs from provided multi-format datasets, meet the updated RML conformance requirements, and/or demonstrate methodological innovation that improves mapping (re-)usability and expressiveness. The challenge aims to foster comparative insights across tools and techniques, strengthen interoperability, and push knowledge graph construction beyond established practices through rigorous evaluation and practical, reusable solutions.

To participate, please fill out this form https://forms.gle/smzqTe67HBemEM3t6 by February 28th.

Format
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Authors can choose the best way to express their work, such as HTML or PDF. However, a CEUR layout<https://ceurws.wordpress.com/2020/03/31/ceurws-publishes-ceurart-paper-style/> has to be provided.

Important dates (AoE)
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Interest in participation in the Challenge: 28th February 2026
Paper Submission: 3rd March 2026
Acceptance Notification: 31st March 2026
Camera-ready Version: 15th April 2026
Workshop: 10th-11th May 2026

Organising Committee
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David Chaves-Fraga, USC (contact person: david.chaves@usc.es<mailto:david.chaves@usc.es>)
Anastasia Dimou, KULeuven
Christophe Debruyne, ULiège
Enrique Iglesias, Leibniz University Hannover
Sitt Min Oo, Ghent University
Adrián Martínez-Balea, USC

More news at: https://bsky.app/profile/kgcworkshop.bsky.social



[CiTIUS]<http://citius.usc.es/>
David Chaves-Fraga<http://citius.usc.es/v/david.chaves>
Assistant Professor - Univ. Santiago de Compostela
[E-mail:]<mailto:david.chaves@usc.es> david.chaves@usc.es<mailto:david.chaves@usc.es> · [Phone:]  +34 8818 16436
Intelligent Systems Group<https://investigacion.usc.gal/grupos/4637/detalle> · Personal Website<https://davidchavesfraga.com/>