Knowledge Graphs are very hot in the information world right now; when articles from this fairly esoteric space in the information industry show up in Forbes and the Wall Street Journal, something is clearly afoot.
Why is this? How do Knowledge Graphs purport to help us (and, apparently, large corporations) make sense of things?
Naturally, this requires some firming up of definitions: What is a Knowledge Graph? Is it an ontology? A specific kind of ontology, with specific features? Or an ontology with a specific purpose? Or: Does a Knowledge Graph have to include Linked Data? Or: Does it have to be query-able?
Having sussed out some of these taxonomic outlines, it is then time to ask: how do Knowledge Graphs (or their advocates) purport to help with sense-making?
Key takeaways from the session:
- What are Knowledge Graphs? And what are they useful — and not useful — for?
- Can we really model the sum of human understanding using Knowledge Graphs? (Because that would be cool!)
- Well, no.
- But we *can* do lots of useful sense-making using this set of technologies and techniques, including (importantly) pointing (electronically) to sense already made by others.
About the speakers
Bob Kasenchak’s interest in information science began while working at Schwann Publications in the late 1990s. Publishing a quarterly phone-book-sized classical music catalog featuring carefully controlled synonymic records and standardization of terms suggested the necessity for hierarchical data structures in the service of organizing information about composers and musical works. After a decade studying and teaching music, Bob spent 8 years designing and developing information projects at a leading taxonomy firm before joining Synaptica in 2019.