Knowledge bases, data bases and object-oriented systems (referred to in the paper as Object-Centered systems) all rely on attributes as the main construct used to associate properties to objects; among these, a fundamental role is played by the so-called part-whole relation. The representation of such a structural information usually requires a particular semantics together with specialized inference and update mechanisms, but rarely do current modeling formalisms and methodologies give it a specific "first-class" dignity. The main thesis of this paper is that the part-whole relation cannot simply be considered as an ordinary attribute, its specific ontological nature requires to be understood and integrated within data modeling formalisms and methodologies. On the basis of such an ontological perspective, we survey the conceptual modeling issues involving part-whole relations, and the various modeling frameworks provided by knowledge representation and object-oriented formalisms.

There is a growing recognition that partwhole hierarchies are a very general form of representation, widely used by humans in commonsense reasoning. This paper develops a terminological logic, and related inference mechanisms for representing and reasoning about composite concepts and individuals. A basic terminological logic language is extended with constructs for describing composite concepts in terms of their parts and the relationships between them. A part-of hierarchy is defined, based on the relationship of compositional inclusion. This partof hierarchy is analogous to, but different from, the "is-a" hierarchy. Compositional inferencing is defined as a process which infers the existence of a whole, based on the existence of the required parts, where the parts are in the necessary relationship to each other. Three stable states are defined with respect to compositional inferencing - compositional extensions, credulous compositional extensions and skeptical compositional conclusio...

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