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the rules (laws, regulations, or mores) of a society. These definitions are common in the ontology and
data-modeling literatures (Wand et al. 1999; Sowa 1999; Guarino and Welty 2002).
There is a duality between events and states. Events cause states to change (including the event that
brings an object into existence), and states reflect the effects of events. Conceptually, it is possible to
derive the state of an object at time t1 from its state at time t0 and the events that have occurred between
t0 and t1 by the application of event rules and data. However, it is not always possible to derive the event,
the rules, and data from the states of an object at times t0 and t1. If the sole purpose of an information
system is to record and report on states that have been observed or proposed in some domain, then
deriving and tracking events may not be important. We term such state-tracking information systems
“passive” because they do not participate in the organizational system. They do not calculate, infer, or
predict the states of objects; they simply report on observations or proposed states.
Information systems that exhibit intelligence typically go beyond the recording of states. They
ascribe state to objects by applying rules associated with defined and identified events (Geerts and
McCarthy 2002). Events and their rules are a significant focus in such information systems. We term
such event-processing information systems “active” because they participate in the determination of
states rather then simply record observations or determinations of state made outside their scope. Pas-
sive information systems are most appropriate for dealing with natural systems, where the interest is
in tracking the changes in properties of physical objects. Bunge (1977) uses the terms concrete object
or thing for such physical objects. Immutable natural laws govern the way the properties of physical
objects change. Active information systems are most appropriate for artificial systems, where the inter-
est is in taking action. Organizationally or socially constructed (Searle 1995, 2006) rules govern the
actions that result in changes to conceptual (socially constructed) and concrete objects (Hirschheim,
Klein, and Lyytinen 1996).
Active information systems need not implement the state-change rules for all events in the domain
they are intended to model. The causal rules that govern state transitions when an event occurs may
be unknown, or they may not be of concern to the stakeholders (Ramesh and Browne 1999). For such
events, the “rule” may be null. Its description may simply specify new or incremental values that define
the subsequent states of the affected objects. In that sense the active, event-processing conceptualization
of an information system subsumes the passive, state-tracking conceptualization. Furthermore, it allows
for flexibility to later extend an information system by adding intelligence to events as needed.
ontology of events
The ontological definition of event has been the source of much philosophical debate, as described
below:
Broadly understood, events are things that happen—things such as births and deaths, thunder and light-
ening, explosions, weddings, hiccups and hand-waves, dances, smiles, walks. Whether such things form
a genuine metaphysical category is a question that has attracted the sustained interest of philosophers,
especially in the second half of the 20th century. But there is little question that human perception, ac-
tion, language, and thought manifest at least a prima facie commitment to entities of this sort . . .
Although not undisputed, some standard differences between events and physical objects are com-
monplace in the philosophical literature. First, there is a difference in mode of being: material objects
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