29 September 2022, Emanuele Laurenzi, 1 view
Abstract:
Artificial Intelligence – be it data-driven or explicit AI – has the potential to revolutionize the way we work. A form of explicit AI, knowledge graphs deliver connected insights across functional or use case boundaries and drive knowledge democratization in the enterprise. Because they support the explicit modeling of knowledge traditionally hidden in complex processes, long documents, domain-specific applications, or domain experts’ minds, they are a great foundation for trustworthy and explainable business decisions and processes.
In this tutorial, we will present the gold standard approach to explicit knowledge modeling (semantic modeling) which transforms the creation of a knowledge graph into a streamlined, end-to-end process where all relevant stakeholders – from IT experts and ontology engineers to domain experts and business users – are equally involved. This approach is based on metaphactory’s visual and user-friendly interface for creating, exploring, visualizing, editing, and documenting knowledge graph assets such as ontologies, taxonomies, or data catalogs. The visual language translates to core elements of OWL, SHACL and SKOS and results in knowledge graph assets based on open and flexible W3C standards.
To make the tutorial as use case driven as possible, we will look at explicit knowledge modeling in the context of skill management and will cover the following topics:
See also: https://www.makeathonfhnw.ch/tutorials-pre-makeathon/
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