Taxonomy Boot Camp Connect 2020
Virtual (online event)Taxonomy Boot Camp is the world's leading conference dedicated to exploring the successes, challenges, methodologies and products for taxonomies.
Conferences and other events about knowledge graphs, linked data and related topics
While every effort has been made to keep these listings current, in light of the COVID-19 pandemic always check the linked event site for the most up-to-date information concerning that event.
Taxonomy Boot Camp is the world's leading conference dedicated to exploring the successes, challenges, methodologies and products for taxonomies.
This webinar will address the role of taxonomies in recommender systems, including how taxonomies may be enriched to convert them into basic knowledge graphs.
Knowledge Connexions 2020 will feature three days of workshops, masterclasses and presentations on graph databases, semantic technology, knowledge graphs and graph AI.
Linked Pasts 6 is a conference focused on linked open data as applied to the study of the ancient and historical worlds.
This online meeting, organized by DAFNI, will share work on digital twins and ontologies as well as enabling facilities and ways of thinking.
This webinar will describe the difference between data models, metamodels, and ontologies, and explore the fundamental information model that underpins systems engineering.
This tutorial for DBpedia developers includes information on replicating local infrastructure and the new DBpedia Stack.
This meetup is the public forum where these reports from the Metaspace practitioners workshop will be presented, along with live Q&A from the audience, for metadata questions answered by a collection of industry expert practitioners.
This webinar will present a case study of a targeted content recommendation engine, along with information on the fundamental principles of taxonomy and ontology design as the backbone to the AI solution.
This Data Science Central webinar will address design considerations and deployment best practices for three case studies that combine knowledge graphs with machine learning.