Yesterday, about 20 people gave up 4 hours of sunny Saturday afternoon to gather in Carlsbad to listen to Jans Aasman present a tutorial on AllegroGraph - what Franz Inc. is touting as "Web 3.0's Database". The attendees, some of whom drove all the way down from Santa Barbara, included a number of people interested in semantic search and search engine optimization. There were also software developers, CEOs of software development companies, bioinformaticians, an orthopedic surgeon, business development specialists, and entrepeneurs. A challenging crowd to give a tutorial too that all would find useful.
Since I ended up having to take my notes on my iphone and the presentation lasted nearly 4 hours, I'm only going to hit a couple of the things that stood out for me here. For more info. on the products presented, the Franz Inc. website has extensive information - and free downloads! I also hope to find a link to the slides at some point.
First of all, wow - well done organizer! Its not everyday that you get to hear a presentation by the CEO of one of the oldest (is it the oldest?) living companies involved in artificial intelligence. (Yeah I said it.. thats what we used to call this stuff.) Franz has apparently weathered the storm and now that semantics is coming back to life under a new name - has come out doing very well with clients including: Lilly, GlaxoSmithKline, Adobe, Raytheon, Kodak, Boeing, Cisco, Mayo clinic, Novartis, and many others. These clients are paying for the pro versions of tools like AllegroGraph and Gruff as well as consulting services related to the use of these tools to solve specific problems. Jans began his presentation with a really rapid explanation of why these companies are spending their money like this rather than on continued development with the encumbent technology - relational databases.
Jans suggested that triple stores like AllegroGraph are more useful then relational databases when any of the following constraints are met:
- You have many classes of complex objects
- The properties/definitions of these classes change frequently
- You want to work with rules/reasoning
- You have a big graph in your data that you want to analyze
After that brief, high-level motivator he dived into a fairly extensive series of demos/examples. While the subject matter varied from news stories to clinical trials to digital photo websites, there were two consistent themes that I found interesting.
- Every example he gave involved a named entity extraction step at one point or another. This indicates that, while there is a growing amount of structured data out there, there is still way too much information held in text to ignore when doing any real analysis. So.. you are going to need to get friendly with some people that do natural language processing - perhaps like this company Alchemy.
- Most of the demos were conducted in Gruff, the visual interface to AllegroGraph. In Gruff, he repeatedly showed off the very cool trick of selecting two, apparently unrelated nodes in the graph (say a two different drugs) and asking for connections between them. AllegroGraph responded to this request ~instantaneously with relevant and useful results. Very impressive technically (this was a graph with millions of triples and the system was running on his laptop) and I think very useful for discovery.
Wish I could write more but its the weekend after all.. For more information on this stuff, go to Franz inc., grab yourself a free download or two, and try it out yourself! I'd be curious to hear how you find it.