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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.
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