Fifth International Workshop on Knowledge Graph Construction

Co-located with the ESWC 2024

Hersonissos - 26/27th May 2024

See Call for Papers

KGC Call for Papers

More and more knowledge graphs (KGs) are constructed for private use, e.g., Google, or public use, e.g., DBpedia, Wikidata. While many solutions were proposed to construct KGs from existing data on the Web, there is still no mature systems to automate the rules definition nor systematic evaluations to compare the performance and resource usage of the different systems independently of the mapping language they use or the way they construct the knowledge graph (materialization or virtualization). Addressing the challenges related to KG construction requires both the investigation of theoretical concepts and the development of systems and methods for their evaluation.

The Knowledge Graph Construction Workshop (KGCW) has a special focus this time on novel techniques, frameworks, architectures, and tools for the new extensions of RML such as RDF Collections and Containers, and RDF-Star support and the newest version of the RDF Mapping Language (RML) in general.

The workshop includes a keynote, as well as (research, in-use, experience, position, system) paper presentations, demo jam, and break-out discussions. This year, we will celebrate the 2nd edition of the KG Construction Challenge, where an evaluation setup will be provided to the participants to compare the different systems for KG construction.

Our goal is to provide a venue for scientific discourse, systematic analysis, and rigorous evaluation of languages, techniques, and systems, as well as practical and applied experiences and lessons learned for constructing knowledge graphs from academia and industry. The workshop complements and aligns with the activities of the W3C Community Group on KG construction.


  • Automation for Knowledge Graph Construction
  • Conversion of data labelling methods into declarative KGC approaches
  • (Semi)automatically generate mappings
  • Explainable automated knowledge graph generation
  • LLMs supporting (declarative) knowledge graph generation
  • Mapping based Knowledge Graph Construction
  • Mapping languages for constructing Knowledge Graph from legacy datasets
  • End User Interfaces (UI) for (collaborative) editing and viewing for Knowledge Graphs building rules and management platforms in general
  • Approaches and techniques on
  • collaborative mappings generation
  • exploiting mappings for query answering
  • Tools for Knowledge Graph Construction
  • Architectures for Knowledge Graph construction systems
  • (Sustainable) workflows for Web scale Knowledge Graph construction & publishing
  • Methods and Techniques for Knowledge Graph Construction
  • Seamless (distributed) integration/interlinking from heterogeneous data sources
  • Dynamic discovery and retrieval of data for KG construction
  • Quality, Provenance, privacy and trustworthiness of Linked Data construction
  • Knowledge Graph construction and publishing of streaming data at run-time
  • Benchmarks for Knowledge Graphs construction and publishing
  • Lessons learnt, In Use and Experience
  • Experience, lessons learnt and best practices for generating and publishing
  • Negative results and in-use/applied descriptions

Authors Guideline


Authors can choose the best way to express their work, such as HTML or PDF. However, a CEUR layout must be provided. If your contribution will be in HTML, you can find some available tools in the ESWC24 HTML guideline.


  • Full research papers (12-15 pages)
  • In Use and Experience papers (12-15 pages)
  • Short research papers (5-8 pages)
  • Challenge papers (6-8 pages)
  • Position and Vision papers (4-6 pages)
  • System/demo papers (4-6 pages)
  • Abstract from journal papers (2-4 pages)

Review and Publication

Please, share your contribution before the deadline through the OpenReview platform. The accepted contributions will be published in the proceedings of the workshop through CEUR-WS. Each accepted paper needs to be presented by one of the authors at the workshop (virtual presentations are not allowed).


Knowledge graph construction of heterogeneous data has seen a lot of uptake in the last decade from compliance to performance optimizations with respect to execution time. Besides execution time as metric for comparing knowledge graph construction, other metrics e.g. CPU or memory usage are not considered. This challenge aims at benchmarking systems to find which RDF graph construction system optimizes for metrics e.g. execution time, CPU, memory usage, or a combination of these metrics.

All details regarding the challenge will be ready soon, please confirm your interest to participate in the challenge by filling out this form before January 31th 2024 AoE. Participating without filling out this form is not possible because we need to arrange hardware for participants.

Workflow for submissions of the Challenge:
  1. Interest for participation by January 31th 2024 AoE.
  2. Results submission by April 30th 2024 AoE (details for submission will be provided soon).
  3. OPTIONAL (Proceedings):
    • Submit report paper by May 12th 2024.
    • Report paper will be reviewed by PC/OC.
    • If paper is accepted, it will be published within the proceedings of KGCW.
    • Camera ready submission by May 24th 2024.

At least one author of each tool needs to present the results during the workshop
(virtual presentations are not allowed)



Important dates

29 February, 2024

Abstract submission

Submit your abstract (optional but recommended)

15 March, 2024

Submission papers

Submit your paper

15 April, 2024


The notification and reviews from our Program Committee will be available.

18 April, 2024

Submission camera ready

Time to have your paper ready for being published. All the accepted paper will be published in the proceedings.

26/27 May, 2024


Keynote, papers presentations, and a lot of discussion. Remember! If your contribution is accepted, it needs to be presented by one of the authors at the event.


Anastasia Dimou

Assistant Professor, KU Leuven

David Chaves Fraga

Assistant Professor, CiTIUS - USC

Umutcan Serles

Postdoctoral Researcher, STI Innsbruck

Dylan Van Assche

PhD Student, imec - IDLab (UGent)

Ana Iglesias Molina

PhD Student, OEG - UPM
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