There are various sources of uncertainties associated with event processing - here is an attempt to list some of them:
Uncertainties related to the source:
- Uncertainty that an event happened due lack of credible source, or inaccuracy in the source reporting (e.g. has the sensor really detected an object, or there has been some power failure in the process).
- Uncertainty to classify an event that happened (murder? suicide? accident?)
- Uncertainty about a value of a certain attribute in the event (again - inaccuracy of measurement or lack of information)
- Uncertainty about the timing of an event (happened sometimes during last night, but we don't know when).
- Uncertainty that our sources reported all events (we cannot assume "closed world")
- Events that are inherently probabilistic (e.g. future/predicted events).
Uncertainties related to the processing:
A pattern in the event history designates a "business situation" in the application domain
- Uncertainty whether the pattern detection is a sufficient condition to identify the situation, or it is only an approximation (which is a major source for "false positives" and "false negatives").
- Uncertainty about the meaning of a "partial satisfaction" of the pattern, e.g. the pattern consists of a conjunction of four events, what happens if three out of the four occur ? is it a really a binary game?
- Uncertainty that is driven by one of the uncertainties related to the source (e.g. uncertainty in the timing of event occurrence may inflict uncertainty in a temporal-oriented pattern).
- Processing of probabilistic events.
There are also uncertainties associated with the event consumer - but there are for now outside the scope of this discussion. More - Later.