March 9, 2023
Paper submission deadline
April 13, 2023
Notification of acceptance
April 20, 2023
Camera-ready version due
May 28 or 29, 2023
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
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.
- 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.
Papers must be submitted via the following EasyChair link no later than March 9th 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.
The workshop is organized by the following people.
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
Research Associate, WU Vienna
Amr is a final year PhD student in informatics at TU Vienna, Austria, Additionally, he is a teaching and research associate at WU Vienna. 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
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
Professor, Aalborg University
Katja is a professor in the Department of Computer Science at Aalborg University, Denmark, where she is 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
The program committee consists of the following people.
|Aidan Hogan, DCC, Universidad de Chile|
|Beatriz Esteves, Universidad Politécnica de Madrid|
|Gabriela Montoya, Aalborg University|
|Hala Skaf-Molli, University of Nantes - LS2N|
|Jürgen Umbrich, Vienna University of Economy and Business (WU Vienna)|
|Maria-Esther Vidal, Technical Information Library Leibniz (TIB)|
|Maribel Acosta, Ruhr University Bochum|
|Matteo Lissandrini, Aalborg University|
|Pascal Molli, University of Nantes - LS2N|
|Peter Haase, metaphacts|
|Ruben Taelman, Ghent University – imec|
|Sebastián Ferreda, Linköping University|
|Sijin Cheng, Linköping University|
|Stasinos Konstantopoulos, NCSR Demokritos|