I just recently attended a meeting about something that many people are beginning to hear about but which most people do not understand — Ontology for Big Systems.

Even the words describing the outcome of meeting are misleading: Summit and Communique. A summit is usually a global meeting of world leaders and a communique is usually a short statement for the public and press. This year’s communique is 11 pages long, which has grown from previous years: 2006 – 1, 2007 – 4, 2008 – 8.4, 2009 – 8.4, 2010 – 8.6, and 2011 – 8 pages.

Ontology has two definitions — one from philosophy and another computer science. I won’t even bother you with their definitions because the Intelligence Community prefers to use the word Knowledge Base instead to describe a collection with a very large number of documents that can be analyzed and searched “for more needles in bigger haystack.”

So what did this meeting hope to accomplish?

I had a hard time figuring that out by reading the draft communique. But what is obvious is something that is hard to understand, Ontology, is being put forward as a solution for “big systems” and for “big data” as though this is something new or not well known.

The fact is that “big (and complex) systems” have been studied and built for a long time now only to re-discover Gall’s Law that I have written about recently using a Department of Defense System of Systems example. Gall’s Law says:

“A complex system that works is invariably found to have evolved from a simple system that worked. The inverse proposition also appears to be true: a complex system designed from scratch never works and cannot be made to work. You have to start over, beginning with a simple system.” – John Gall, systems theorist
The key points to take away from his Law are:
  • All complex systems that work evolved from simpler systems that worked.
  • If you want to build a complex system that works, build a simpler system first, and then improve it over time.
  • Gall’s Law is why prototypes and iteration work so well when creating value.
  • Creating a complex system from scratch is sure to end in failure.
This raises questions worth considering for many program and project managers:
  • Are you trying to build a complex system from scratch?
  • Could you start with a simpler system that already works, then build upon it?
You can read about the meeting’s proceedings and draft communique and wonder what it all means and how to apply it to solve real problems.

As one participant in the meeting said: “Nice Website!!! Was an ontology used to create this website? If so, it would be instructional if there is presentation on how it was done. If the Ontology Summit can use Ontologies in its business, it will make a good business case on the advantages of Ontologies to take it to the Executives.” There has been no response to that suggestion so I did it.

A revealing statement in the draft communique is: In those applications where the ontology will impact end users, there is broad consensus that the details of the ontology be hidden. A final conclusion of the draft communique is: Pragmatically “big systems” and “big data”, especially from a cost perspective, have little technological recourse but to exploit the benefits to be gained from the use of ontology and ontological analysis.

To me this almost sounds like a plea to please use ontology for “big systems” and “big data” so ontologists will be included in these exciting new fields of endeavor, instead of showing what ontology can do for them. I have attended and written about a number of “big data” meetings recently and not heard the word ontology mentioned — the keys words now are data science and knowledge bases. I have heard more reasons for not using ontology than for using them when it comes to processing “big data” with speed from the experts I have talked to.

To me the most encouraging statements came from representatives of the multi-agency Networking and Information Technology Research and Development (NITRD) Program. Wendy Wigen, NITRD Technical Coordinator for the Big Data Senior Steering Group, speaking on the Big Data Challenge, said NITRD is working on Building a Data Science Community.

Dr. George Strawn, Director of the of NITRD Program, panelist for Ontology for Big Systems — Promises and Challenge, said: Semantic Medline is the “killer app” knowledge base that uses ontology but is not well-known yet. Work in progress will hopefully make it more well-known.