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Abstract:
The most influential work in the application of ontology to conceptual modeling is that of Wand and Weber (1990, 1995) who used the ontology posed by Mario Bunge (1977). However, Bunge's ontology is concerned with representing the material world - the world of material objects that possess physical properties existing independently from human perception. It has no place for human intentions, interpretations, creations, or meaning. It is unconcerned about institutional reality - the world of conceptual objects and attributes created by human intentions and for human purposes. Examples of such conceptual objects are corporations, government agencies, money, educational institutions, contracts, and transactions. None of these are material objects about which Bunge's ontology is concerned yet they are at the core of what business organizations are. Lacking constructs for such objects, Bunge's ontology is an inappropriate foundation for conceptual modeling in the context of organizational information systems.

conceptual modeling, ontology, concrete object, conceptual object

Abstract:
Organizations and the information systems that support them are artificial and intentionally designed artifacts. Policies and procedures created by an organization define how specific events affect the states of things about which the organization is concerned. Active information systems are designed to participate in the operation and management of organizational processes. They calculate and ascribe state to material and artificial things according to rules designed by the organization and activated when identified events occur. The ontological definition of an event as a state-transition proscribes the representation of events as entities. The resultant conceptualization of an information system as a state-tracking mechanism obscures the critical role that events play in active information systems. Effective analysis and design of such systems requires a more substantive ontological definition of an event as an entity having both identity and properties. Included in an event's properties are the rules that govern state transitions caused by the event. The resultant conceptualization of an information system is an event-processing mechanism, actively interpreting and re-interpreting events with respect to extant and posed rules. This ontological definition treats things and events uniformly as entities enabling them to have appropriate representations at the conceptual level. It provides a context in which learning can be represented through the definition, identification, and classification of critical events and the evaluation and evolution of rules governing their effects. Additional research is needed to develop and evaluate conceptual modeling grammars and methods that implement this event conceptualization within an information system development methodology.

Data modeling, event construct, ontology

Abstract:
Information systems are integral to the management of business and organizational processes. They perform calculations and ascribe values to material and artificial things according to rules designed by the organization and activated when identified events occur. The ontological definition of an event as a state-transition results in the conceptualization of an information system as a state-tracking mechanism. It precludes the representation of events as entities at the conceptual level. Hence, the rules which are often central to the operations of the organization have no conceptual representation. A more substantive ontological definition of an event as an entity having identity and properties results in the conceptualization of an information system as an event-tracking mechanism, giving events and the rules that govern state-transitions the appropriate, central representation at the conceptual level.

Conceptual data modeling, event construct, ontology

Abstract:
Domains for which information systems are developed deal primarily with social constructions - conceptual objects and attributes created by human intentions and for human purposes. Information systems play an active role in these domains. They document the creation of new conceptual objects, record and ascribe values to their attributes, initiate actions within the domain, track activities performed, and infer conclusions based on the application of rules that govern how the domain is affected when socially-defined and identified causal events occur. Emerging applications of information technologies evaluate such business rules, learn from experience, and adapt to changes in the domain. Conceptual modeling grammars aimed at representing their system requirements must include conceptual objects, socially-defined events, and the rules pertaining to them. We identify challenges to conceptual modeling research and pose an ontology of the artificial as a step toward meeting them.

conceptual modeling, ontology, concrete object, conceptual object, social reality, artificial systems