DMKG2024

2nd International Workshop on Data Management for Knowledge Graphs
Co-located with the ESWC Conference 2024 in Hersonissos, Greece

Important Dates




Deadlines have been extended

March 14, 2024

Abstract submission deadline (new date)

March 7, 2024

March 21, 2024

Paper submission deadline (new date)

April 4, 2024

Notification of acceptance

April 18, 2024

Camera-ready version due

May 26 / 27, 2024

Workshop date

All deadlines are 23:59 Anywhere on Earth (UTC-12)


Call for Papers

The rapid increase in the adoption of knowledge graphs over the past years, both in the open data domain as well as the industry, means that data management solutions for knowledge graphs today have to support ever increasing amounts of data.

The continously growing KGs resulting from the increasing popularity of semantic technologies highlight the necessity for scalable and efficient solutions for management of knowledge graphs in distributed, federated, and centralized environments.

The DMKG workshop therefore invites novel research and advances in scalable data management solutions for large-scale knowledge graphs. Such data management solutions include techniques for storage and indexing, partitioning for decentralized/centralized systems, archiving and versioning, validation with SHACL/shEx, or federated data management. We welcome a broad range of papers including full research papers, vision papers, negative results, and system demonstrations.

The main goal of the workshop is to bring together both early-stage and established researchers as well as industrial partners in order to facilitate communication and collaboration between partners in different domains on the issues relating to scalable data management techniques for large-scale knowledge graphs.

We seek contributions covering all aspects of data management for knowledge graphs, including, but not limited to, the following topics:

Storage and Management

  • Storing and indexing knowledge graphs
  • Partitioning knowledge graphs
  • Decentralized, distributed and federated knowledge graph storage
  • Graph databases and NoSQL
  • Archiving and versioning

Analytics and Exploration

  • Knowledge graph validation (SHACL/shEx)
  • Graph schema discovery and exploration
  • Large-scale knokwledge graph analytics (GraphX, Giraph, Pergel, ...)

Querying and Benchmarking

  • Efficient query processing
  • Distributed and federated querying over knowledge graphs
  • Querying over streaming graphs
  • Benchmarking data mangement systems for knowledge graphs

Submission Instructions

We welcome a broad range of papers to the DMKG workshop. All papers must be original and not simultaneously submitted to another journal, conference, or workshop. We welcome the following paper categories (page limits include references):

  • Research papers (up to 12 pages): Papers presenting significant scientific research pertaining to the topics specified above, incl. vision papers.
  • Short papers (up to 6 pages): Position papers, negative results and papers describing systems, libraries, APIs and datasets.
  • Demo/poster papers (up to 4 pages): Papers demonstrating systems or scientific results not significant enough for a full research paper.
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Submission must be in English and formatted in the style of CEURART by CEUR-WS. For more information on using the CEURART style (single column), please visit the author guidelines. We accept PDF submissions.

Papers must be submitted via the following EasyChair link no later than March 7th at 23:59 Anywhere on Earth (UTC-12). All submissions will be reviewed by members of the program committee. Papers will be evaluated according to their significance, novelty, originality, technical contributions, writing style, clarity, and relevance the the topics of the workshop.

Accepted papers will be published as Open-Access using the CEUR-WS portal and indexed by DBLP. At least one of the authors of each accepted paper is required to register at ESWC 2024 and present the paper.




Organizing Committee

The workshop is organized by the following people.

team member
Assistant Professor, Aalborg University

Christian is an Assistant Professor at Aalborg University. Previously, he has worked with storage, partitioning, versioning, and archiving of knowledge graphs in the decentralized setup, where he created novel architectures and techniques to manage RDF data in the setup. Moreover, he created novel query optimization techniques that increase query performance and scalability for such decentralized systems managing knowledge graphs.

@Chraebe
@chraebe@mastodon.world
team member
Associate Researcher, WU Vienna

Amr is a Research and Teaching Associate in Informatics at WU Vienna, Austria. Before his PhD studies, he worked as a Research Scientist at Nile University and Cairo University. Besides his academic career, he worked as a data scientist for 4 years at IBM. The current focus of his research is on scalable knowledge graphs, Web querying, and graph data management systems.

@AmrTarekAzzam
team member
Senior Associate Professor, Linköping University

Olaf is a Senior Associate Professor in Computer Science at Linköping University, Sweden. Additionally, he is an Amazon Scholar working with the Neptune graph database team at Amazon Web Services. He is interested in problems related to the management of databases and knowledge, with a focus on data on the Web and on graph data, as well as on problems in which the data is distributed over multiple, autonomous and/or heterogeneous sources.

@olafhartig
team member
Professor, TU Wien

Katja is a professor in the Institute of Logic and Computation at TU Wien, Austria. She has been a professor in the Department of Computer Science at Aalborg University, Denmark, leading the Data, Knowledge, and Web Engineering group. Prior to joining Aalborg University, she was a postdoc at the Max Planck Institute for Informatics in Saarbrücken, Germany, and earned her PhD in Computer Science from Ilmenau University of Technology, Germany. Her work is rooted in databases and graph technologies and spans theory, algorithms, and applications of data science and knowledge engineering including knowledge graph management, querying, and analytics.

@HoseKatja
@katjahose@mastodon.social

Program Committee

The program committee consists of the following people.

PC Members
To be announced.