In this workshop we will take a closer look at how the interaction between manually created parts of a knowledge graph and an automatically generated data graph can be managed and organized. Learn how semantic knowledge models and machine learning can go hand in hand and enable the creation of knowledge graphs on a large scale. Get a comprehensive overview of different semantic AI applications based on knowledge graphs and see how a semantic middleware platform like PoolParty can be integrated into different architectures to run them.
We will start the workshop by outlining the basics for the use, standards, design and creation of knowledge organisation systems (conceptual models, taxonomies, thesauri and ontologies). Practical exercises will focus on best practices for creating semantic knowledge models. We will give examples based on card sorting methodology, show how to translate this initial structure into enterprise taxonomies and how ontologies can be embedded.
On this basis, we will take a closer look at how the anatomy of a knowledge graph looks, which parts can be processed automatically, where machine learning can help and which components still need to be created and curated by knowledge engineers and subject matter experts. We will also discuss the principles of human-in-the-loop design and explainable AI (XAI). The topics covered are:
In the third and final part of the workshop, we will highlight the various possibilities for successfully using knowledge graphs in companies. We will focus on application scenarios in various industries such as financial, pharmaceutical, media, e-commerce, IT & consulting, and also address the question of how a possible governance model for the knowledge graph can be embedded in the enterprise data governance model.
All participants of the workshop will receive a free copy of The Knowledge Graph Cookbook, which will be published in April 2020.