Fourth International Workshop on Knowledge Graph Construction

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.

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.

In this keynote, I will present the journey from the research group at the Free University of Bozen-Bolzano developing Ontop, an open-source virtual knowledge system, to Ontopic, a company dedicated to bringing this technology to the industry. I will discuss our take on knowledge graph construction and mappings, which led us to build our first product, Ontopic Studio, a no-code R2RML mapping editor. In particular, I will highlight what is essential for building efficient virtual knowledge graphs and explain how we extend the existing standards to address advanced needs. To conclude my talk, I will share important lessons we learned from industry and discuss current trends.

About the speaker

Benjamin Cogrel is CTO and co-founder of Ontopic, a spin-off from the Free University of Bozen-Bolzano specialized on Virtual Knowledge Graphs and Knowledge Graph Construction. He is also one of the main developers of Ontop, the most popular open-source Virtual Knowledge Graph engine. Prior to founding Ontopic, Benjamin was a postdoc from 2014 to 2019 at the Free University of Bozen-Bolzano, where he worked on Virtual Knowledge Graphs and brought important contributions to Ontop. He received his PhD in Computer Science at the University of Paris-Est in 2013.