Conceptual Modeling of Events for Active Information Systems - Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications - page 269

activity may depend not only on the event under consideration but also on other events, and possibly on
temporal and relational aspects of those events.
Consider, for example, a person who has purchased a large quantity of ammonium nitrate fertilizer
(initiated a “purchase fertilizer” event). If the person has no prior terrorist engagements (no “terrorist
engagement” events) and regularly purchases fertilizer (has a number of prior “purchase fertilizer”
events), then the rule may specify that this event has no effect on the likelihood of terrorist activity
for that person. Conversely, if this is the first time the person has purchased fertilizer and the person
has recently purchased other materials related to the production of explosives or is associated with a
group that has other members who have recently purchased these materials, then the rule may specify
a significant increase in the probability of terrorist activity. Data and rules of this type are consistent
with the development of “probable cause” required for a law enforcement agency to take action. How-
ever, if we do not find out about the other purchases (events) until a later time, we must reanalyze the
historical event stream and develop a new state history, possibly leading to a different conclusion and
different actions.
Finally, we observe that an ontology is an artifact, developed by human intention for specific pur-
poses (Gemino and Wand 2005). Philosophically, an ontology can be evaluated by “how well” its con-
structs enable the description and representation of the natural (physical) world. Within the scope of
information systems, however, the purpose of ontology is to enable the development of more effective
information systems (Bodart et al. 2001; Bowen et al. 2004; Allen and March 2006). We believe that
ontologies constructed to represent natural or physical systems are insufficient to represent artificial
systems because they lack constructs by which to represent conceptual objects, invented (meaningful)
attributes, intentionality, and causal rules that govern state transitions. We have presented the “event as
entity” construct and the conceptualization of an information system as an event-processing mechanism
as foundational to such an ontology.
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subject matter of the IS field. Communications of the AIS, 12 , 365-394.
Alter, S. (2006). The work system method: Connecting people, processes, and IT for business results.
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Bodart, F., Patel, A., Sim, M., & Weber, R. (2001). Should the optional property construct be used in con-
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Bowen, P. L., O'Farrell, R. A., & Rohde, F. H. (2004). How does your model grow? An empirical
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