Video Forum

Knowledge Graphs are long past being only academic. Chris Brockmann, CEO of eccenca, makes the business case for knowledge graphs. He talks about why it is the foundation for automation and artificial intelligence - and explains why both won't fly with relational databases and property graphs only.

As we all know, knowledge graphs do not form themselves, at least not well.

There are countless articles, slide decks and videos on the Internet about knowledge graphs. The topic is examined from different perspectives, e.g., from the point of view of artificial intelligence or in the context of extended possibilities for data analysis or information retrieval.

With the coming of Industry 4.0 and the continuing digitization of manufacturing, construction, oil & gas, automotive etc, a large number of relevant standards have been proposed, approved, put through use cases and interoperability exercises, and some of them found massive adoption in the industry. Older established standards have been integrated or "semanticized", i.e.

In this video, Ahren Lehnert, Senior Manager, Text Analytics and Bob Kasenchak, Senior Manager, Client Solutions from Synaptica, LLC illustrate a case study in which governance and workflow features in their ontology management software, Graphite, use a customized API connector to Confluence to tag content and round-trip concepts between end users and ontology administrators to meet their clien

timbr is the SQL Knowledge Graph platform that enables creation of virtual semantic knowledge graphs mapped to your databases.

Ontologies can help in the digitalization of engineering design processes. We focus on the design and development of spacecraft, in particular on archiving and discovery of spacecraft part specifications. We created an ontology that is used as a skeleton for creating database schemas and data exchange APIs as well as populating a knowledge graph.

If Knowledge is Power, and Data is a means to Knowledge, then it makes sense to hoard data. But what if sharing data makes it more powerful? In this video, I outline four examples where sharing data makes it more valuable and more powerful.

• Our enterprise data challenges: siloed data, inconsistent representation, and varies levels of quality

Taxonomy trends for 2020 include growth in ecommerce taxonomies and intranet/digital employee experience taxonomies. Longer on-going trends include auto-categorization, AI, and machine learning with taxonomies, and the integration/convergence of taxonomies and ontologies. The integration of taxonomies and ontologies is described in more detail.