More and more Knowledge Graphs are generated for private, e.g. Siri, Alexa, or public use, e.g. DBpedia, Wikidata. While techniques to automatically generate Knowledge Graph from existing Web objects exist (i.e., scraping Web tables), the majority need extensive resources. Those with limited resources typically generate Knowledge Graphs by transforming the content of their datasets (RDB, CSV, etc). Initially, generating Knowledge Graphs from existing datasets was considered an engineering task, however scientific methods recently emerged. Lately, mapping languages for describing rules to generate knowledge graphs and processors to execute those rules emerged. Addressing the challenges related to Knowledge Graphs generation requires well-founded research, including the investigation of concepts and development of tools and methods for their evaluation. KGB is a full-day workshop on Knowledge Graph generation with a special focus on Mapping Languages. It is co-located with the Extended Semantic Web Conference 2019 (ESWC2019). The main 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-learnt for generating knowledge graphs from academia and industry.
The increasing number of methods and tool for Knowledge Graph construction mandate consensus for evaluation of these methods and tools. We aim to forge this consensus by assessing strengths and weaknesses of tools, increasing the communication among algorithm developers, and improve evaluation techniques and work on Knowledge Graph construction in general. We aim to achieve this by launching an evaluation campaign that includes the publication of test cases and results of different tools’ evaluation.
This year we focus on the test cases that help assessing the coverage of the different tools. We encourage researchers/developers to submit their results after (one of the following):
From the results, researchers/developers are expected to submit a system paper (6-8 pages using the LNCS style) in the proceedings of the Knowledge Graph Building workshop.
To ensure easy comparability, we suggest that the papers follow this outline:
Authors can choose the best way to express their work, such as HTML or PDF. However, a LNCS-like layout should be provided. If your contribution will be in HTML, you can find some available tools in the ESWC19 HTML guideline.
Please, share your contribution before the deadline through the OpenReview platform. The accepted contributions will be published in the proceedings of the workshop. Each accepted paper needs to be presented by one of the authors at the workshop.
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.
Most of the information showed on this website comes from the KGB2019 RDF Graph. For generating it, we use the RML suite (YARRRML parser and RML-Mapper) and for querying it, we use the Comunica Framework.