Earlier in the day, I spent a couple of hours in my favorite coffee shops, starting chapter 5 of the "Event Processing in Action" book. Writing a book is a major commitment, and since I am doing it in my (imaginary) spare time, this is quite a burden on my time. I had a lunch last week with Roy Schulte from Gartner who is also writing a book (together with Mani Chandy), and he also complained that the book writing messes up all his spare time.
I was asked about the scope of the book, well - the book concentrates on pure event processing. There are some are complementary technologies like -- image processing, text analysis, speech recognition, sensor networks, statistical reasoning, machine learning that can be used to automatically generate either events or patterns (in relative small number of applications at this point), as they are really complementary technologies, they are mentioned briefly in the advanced topics chapter, the main stream of the book is about event processing .
After this long introduction , I'll turn to write about some portion of chapter four of the book which we submitted yesterday to the author. Chapter four deals with the representation of events (meta-data). There are currently no standards about representation of events, thus, we have taken ideas from different directions, to form such a model. We are looking at typed events, thus, each event type has some information particular to event type. We distinguish between three types of such information: header, payload, and event to event relations.
- Header attributes provide information about the event - type, time granularity for the event, and times associated with the event (occurrence time, detection time), event identity and some others.
- Payload attributes provides information about the event content -- references to entities and other attributes
- Event to event relation provides information about semantic relations among events.