Talk:RDF Stream Models

States, facts, complex events and time intervals

"Simple events happen at a single time instant, complex events start and end happening"

MJR: Complex event objects are synthesized events, triggered within the event processing system. Even though the triggering events may have occurred (or have been observed) at different times, there is always a singular point in time with the precision available in the event processing system, at which time all the required events and facts align to trigger the complex event.

Whether or not we want to record the times associated with the triggering events (simple or complex) depends on the case. In the simplest form the complex event can be structurally identical to a simple event and if it is passed onto another event processing network as input, it may indeed be seen as a simple event (single-source, no layering). In the other extreme we may encapsulate all the triggering events into the complex event and forward the complete information. We may also choose to incorporate the times of the first and the last triggering event into the complex event, but that is just one specific case, not a defining factor for complex events.

On the aspect of "start and end happening", any event may trigger a state transition, which can persist as long as another event reverses the transition. I have yet to see a good example on why events would have to have durations, but the state I referred to above could be considered a "synthetic fact" with temporal validity.

Example: N.N. got elected to the parliament (event) => N.N. is a member of parliament (state / fact) => N.N. did not get re-elected (event) => N.N. is not an MP (state/fact).

Temporal graphs

MJR: Is there an example of temporal graphs (any serialization) with multiple timestamps (not intervals)?