Mapping based Knowledge Graph Generation
Methods and Techniques for Knowledge Graph Generation
Mapping languages for generating Knowledge Graph from legacy datasets
Approaches and techniques on (semi)automatically generate mappings
Approaches and techniques on collaborative mappings generation
Approaches and techniques on exploiting mappings for query answering
End User Interfaces (UI) for (collaborative) editing and viewing for Knowledge Graphs building rules and management platforms in general
Architectures for Knowledge Graph generation systems
(Sustainable) workflows for Web scale Knowledge Graph generation & publishing
Seamless (distributed) integration/interlinking from heterogeneous data sources
Dynamic discovery and retrieval of data for KG generation
Quality, Provenance, privacy and trustworthiness of Linked Data generation
Knowledge Graph generation and publishing of streaming data at run-time
Benchmarks for Knowledge Graphs generation and publishing
Experience, lessons learnt and best practices for generating and publishing
Negative results and in-use/applied descriptions
National & Kapodistrian University of Athens
Université Côte d'Azur, CNRS, Inria, I3S
Submit your paper to KGB workshop using the OpenReview platform. You can see the main topics of the Workshop in the Call for Papers.
The notification and reviews from our Program Committee will be available.
Time to have your paper ready for being published. All the accepted paper will be published in the KGB proceedings.
Keynote, papers presentations, demo jam and a lot of discussion. Remember! If your contribution is accepted, it needs to be presented by one of the authors at the workshop.
PhD student at Ontology Engineering Group, Universidad Politécnica de Madrid. His research is focused on virtual Knowledge Graphs generation from heterogeneous data sources exposed on the Web using mapping languages.
Senior/post-doctoral researcher at imec and IDLab, Ghent University. Her research interests include Linked Data Generation and Publication, Data Quality and Integration, Knowledge Representation and Management.
PhD student at imec and IDLab, Ghent University. His research interests include Knowledge Graph and Linked Data Generation, and interaction between users and mapping languages.
Senior/post-doctoral researcher at Ontology Engineering Group, Universidad Politécnica de Madrid. His main research interest is on the generation of Knowledge Graph from legacy datasets.
Juan F. Sequeda is co-founder of Capsenta, a spin-off from his research, and Senior Director of Capsenta Labs. His research interests are on the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management.
Building Knowledge Graphs from Survey Data: A Use Case in the Social Sciences
Leveraging Ontologies for Knowledge Graph Schemas
Building a Knowledge Graph for Products and Solutions in the Automation Industry
RocketRML - A NodeJS implementation of a use-case specific RML mapper
Mapping languages: analysis of comparative characteristics