Fourth International Workshop on Knowledge Graph Construction

Co-located with the ESWC 2023

Hersonissos - 28th May 2023

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 systematic evaluation 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) 2023 has a special focus on the efficiency of the systems during the construction of knowledge graphs, exploring the trade-offs between different approaches (e.g., planification VS physical operators).

The workshop includes a keynote and a panel, as well as (research, in-use, experience, position, tools) paper presentations, demo jam and break-out discussions. In particular this year, we aim to provide an evaluation setup to the workshop participants to compare the different tools for KG construction.

Our goal is to provide a venue for scientific discourse, systematic analysis, and rigorous evaluation of languages, techniques, and tools, 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.


  • Adjusting semantic data labelling methods into declarative KG construction approaches
  • Conversion of data labelling methods into declarative KGC approaches
  • (Semi)automatically generate mappings
  • Explainable automated 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 ESWC23 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 can be found in this link

Workflow for submissions:
  1. Submit an abstract describing your tool before 31 of March 2023 AoE through OpenReview.
  2. Submit results (details for submission will be provided soon)):
    • Submit parameters dataset (Part 1) results before 12th of May (AoE).
    • Submit GTFS-Madrid-Bench (Part 2) results before 19th of May (AoE).
  3. OPTIONAL (Proceedings):
    • Submit report paper AFTER the workshop.
    • Report paper will be reviewed by PC/OC.
    • If paper is accepted, it will be published within the proceedings of KGCW.

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


Program coming soon

Important dates

16 March, 2023

Abstract submission

Submit your abstract (optional but recommended)

23 March, 2023

Submission papers

Submit your paper

17 April, 2023


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

8 May, 2023

Submission camera ready

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

28 May, 2022


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

Senior Researcher, KU Leuven & UPM

Umutcan Şimşek

Postdoctoral Researcher, STI Innsbruck

Dylan Van Assche

PhD Student, imec - IDLab (UGent)

Ana Iglesias Molina

PhD Student, OEG - UPM

Program Committee

  • Aidan Hogan, Universidad de Chile
  • Anelia Kurteva, TU Delft
  • Antoine Zimmermann, École des Mines de Saint-Étienne
  • Ben De Meester, Ghent University – imec
  • Bram Steenwinckel, Ghent University – imec
  • Edna Ruckhaus, Universidad Politécnica de Madrid
  • Enrique Iglesias, L3S & TIB
  • Ernesto Jiménez-Ruiz, University of London
  • Femke Ongenae, Ghent University – imec
  • Franck Michel, Université Côte d'Azur
  • François Scharffe, Columbia University
  • Giorgos Flouris, FORTH
  • Hannes Voigt, Neo4j
  • Herminio Garcia Gonzalez, Kazerne Dossin
  • Jakub Klímek, Charles University
  • Josiane Parreira, Siemens
  • Juliette Opdenplatz, niversity of Innsbruck and Onlim GmbH
  • Jürgen Umbrich, Onlim GmbH
  • Lan Yang, University in St. Louis
  • Manolis Koubarakis, National & Kapodistrian University of Athens
  • Maria-Esther Vidal, L3S & TIB
  • Mario Scrocca, CEFRIEL
  • Maxime Lefrancois, École des Mines de Saint-Étienne
  • Oscar Corcho, Universidad Politécnica de Madrid
  • Pano Maria, Skemu
  • Samaneh Jozashoori, metaphacts
  • Sergio José Rodríguez Méndez, Australian National University
  • Sven Lieber, Royal Library of Belgium (KBR)
  • Vladimir Alexiev, Ontotext