The slides for my Business Rules Forum presentation on event semantics and focusing on events in order to simplify process definition and to facilitate more robust governance and compliance are at Event-centric BPM.
After the talk I spoke with Jan Verbeek and Gartjan Grijzen of Be Informed and reviewed their software, which is excellent. They have been quite successful with various government agencies in applying the event-centric methodology to produce goal-driven processing. Their approach is elegant and effective. It clearly demonstrates the merits of an event-centric approach and the power that emerges from understanding event-dependencies. Also, it is very semantic, ontological, and logic-programming oriented in its approach (e.g., they use OWL and a backward-chaining inference engine).
They do not have the top-down knowledge management approach that I advocate nor do they provide the logical verification of governing policies and compliance (i.e., using theorem provers) that I mention in the talk (see Guido Governatori‘s 2010 publications and Travis Breaux‘s research at CMU, for example) but theirs is the best commercially deployed work in separating business process description from procedural implementation that comes to mind. (Note that Ed Barkmeyer of NIST reports some use of SBVR descriptions of manufacturing processes with theorem provers. Some in automotive and aerospace industries have been interested in this approach for quality purposes, too.)
BeInformed is now expanding into the United States with the assistance of Mills Davis and others. Their software is definitely worth consideration and, in my opinion, is more elegant and effective than the generic BPMN approach.
I’ve been working for a while now on an ontology for representing events (which includes process, of course). One of the requirements of a system that is to monitor, govern, implement, or reason about processes is that it consider “situations”, which are things that happen or occur, including events and states. (See, for example, the perdurants of the DOLCE ontology, BFO‘s occurents, or OpenCyc’s situations.) This requires the representation of time-variant information at various points or during various intervals of time (more than just the Allen relations or OWL Time). If you’re interested in such things, I’d recommend Parsons‘ “Events in the Semantics of English” or Pustejovsky‘s “Syntax of Event Structure“, both of which look at the subject from a linguistic rather than inferential perspective. When you pursue this to the point that you implement the axioms that an artificial intelligence needs to provide assistance in defining or governing a business process (or answering questions about molecular biological processes) you land up in some pretty abstract stuff, including the Stanford Encyclopedia of Philosophy. I found the title of this post entertaining within the page on temporal logic.
Being a fan of increased intelligence on the web, including Bing’s use of Powerset and True Knowledge, I enjoyed cnet’s report, “Google search gets answer highlights and events.”
Google now shows the following “The Empire State Building rises to 1250 ft (381 m) at the 102nd floor” in response to the classic semantic web test question.
Also, Google leverages more of the content of text or structure of linked data in its Rich Snippet answers:
As search engines increase their understanding of concepts and how to extract them from content or linked data and present them as Google does here or above in a sentence, the web will begin to feel a lot smarter.
As these simple enhancements indicate, the intelligent web is taking off and that feeling of intelligence will come sooner than expected. Of course, there is a long way to go. For more on that, I here there is an upcoming issue of AI Magazine that will survey the state of the art in question answering, including coverage of Vulcan’s Project Halo and IBM’s Jeopardy effort, among others. Also, if you are interested in what bright minds are looking forward to in this regard, see Nova Spivak’s recent blogging and his post on “will the web become conscious?”
In preparing for my workshop at the Business Rules Forum in Las Vegas on November 5th, I have focused on the following needs in reasoning about processes, about events, and about or over time:
Reasoning at a point within a [business] process
Reasoning about events that occur over time.
Reasoning about a [business] process (as in deciding what comes next)
Reasoning about and across different states (as in planning)
Enterprise decision management (EDM) addresses the first. Complex event processing (CEP) is concerned with the second. In theory, EDM could address the third but it does not in practice. This third item includes the issue of governing and defining workflow or event-driven business processes rather than point decisions within such business processes.
Business applications of rules have not advanced to include the fourth item. That is to say, business has yet to significantly leverage reasoning or problem solving techniques that are common in artificial intelligence. For example, artificially intelligent question and answer systems, which are being developed for the semantic web, can do more than retrieve data – they perform inference. Commercial database and business intelligence queries are typically much less intelligent, which presents a number of opportunities that I don’t want to go into here but would happy to discuss with interested parties. The point here is that business does not use reasoning much at all, let alone to search across the potential ramifications of alternative decisions or courses of action before making or taking one. Think of playing chess or a soccer-playing robot planning how to advance the ball on goal. Why shouldn’t business strategies or tactical business decisions benefit from a little simulated look-ahead along with a lot of inference and evaluation?
Even though I have recently become more interested in the fourth of these areas, I expect the audience at the business rules forum to be most interested in the first two points above. There will also be some who have enough experience with complex business processes, which are common in larger enterprises. These folks will be interested in the third item. Only the most advanced applications, such as in biochemical process planning, will be interested in the fourth. I don’t expect many of them to attend!
The notion of enterprise decision management (EDM) is focused on point decision making within a business process. For enterprises that are concerned with governing business processes, a model of the process itself must be available to the business rules that govern its operation. I’ve written elsewhere about the need for an ontology of events and processes in order to effectively integrate business process management (BPM) with business rules. Here, and in the workshop, I intend to get a little more specific about the requirements, what is lacking in current standards and offerings, and what we’re trying to do about it. Continue reading “Time for the next generation of knowledge automation”
Complex event processing (CEP) software handles many low-level events to recognize a high-level event that triggers a business process. Since many business processes do not consider low-level data events, BPM may not seem to need event processing. On the other hand, event processing would not be relevant at all if it did not occasionally trigger a business process or decision. In other words, it appears that:
CEP requires BPM but
BPM does not require CEP
The first point is market limiting for CEP vendors. Fortunately for CEP vendors, however, most BPM does require event-processing, however complex. In fact, event processing is perhaps the greatest weakness of current BPM systems (BPMS) and business rules management systems (BRMS), as discussed further below. Continue reading “CEP crossing the chasm into BPM by way of BRMS”