Knowledge Graph Technology and Applications 2019
Last week, on May 13, the Knowledge Graph Technology and Applications workshop happened, co-located with the Web Conference 2019 (formerly known as WWW), in San Francisco. I was invited to give the opening talk, and talked about the limits of Knowledge Graph technologies when trying to express knowledge. The talk resonated well.
Just like in last week's KGC, the breadth of KG users is impressive: NASA uses KGs to support air traffic management, Uber talks about the potential for their massive virtual KG over 200,000 schemas, LinkedIn, Alibaba, IBM, Genentech, etc. I found particularly interesting that Microsoft has not one, but at least four large Knowledge Graphs: the generic Knowledge Graph Satori; an Academic Graph for science, papers, citations; the Enterprise Graph (mostly LinkedIn), with companies, positions, schools, employees and executives; and the Work graph about documents, conference rooms, meetings, etc. All in all, they boasted more than a trillion triples (why is it not a single graph? No idea).
Unlike last week, the focus was less on sharing experiences when working with Knowledge Graphs, but more on academic work, such as query answering, mixing embeddings with KGs, scaling, mapping ontologies, etc. Given that it is co-located with the Web Conference, this seems unsurprising.
One interesting point that was raised was the question of common sense: can we, and how can we use a knowledge graph to represent common sense? How can we say that a box of chocolate may fit in the trunk of a car, but a piano would not? Are KGs the right representation for that? The question remained unanswered, but lingered through the panel and some QnA sessions.
The workshop was very well visited - it got the second largest room of the day, and the room didn’t feel empty, but I have a hard time estimating how many people where there (about 100-150?). The audience was engaged.
The connection with the Web was often rather tenuous, unless one thinks of KGs as inherently associated with the Web (maybe because they often could use Semantic Web standards? But also often they don’t). On the other side it is a good outlet within the Web Conference for the Semantic Web crowd and to make them mingle more with the KG crowd, I did see a few people brought together into a room that often have been separated, and I was able to point a few academic researchers to enterprise employees that would benefit from each other.
Thanks to Ying Ding from the Indiana University and the other organizers for organizing the workshop, and for all the discussion and insights it generated!
Update: corrected that Uber talked about the potential of their knowledge graph, not about their realized knowledge graph. Thanks to Joshua Shivanier for the correction! Also added a paragraph on common sense.
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