A Neutral Semantic Representation for Data Model and Schema Translation

In order to achieve the interoperability of heterogeneous database systems, a semantics-preserving translation of the modeling constructs and constraints captured by different data models and defined in different schemata is a necessity. It is difficult to translate the constructs and constraints of one model directly into those of another model because 1) their terminologies and modeling constructs are often different, and 2) being high-level user-oriented models, their modeling constructs may have a lot of implied semantic properties which may or may not correspond to those of the others. If these high-level constructs and constraints are decomposed into some lowlevel, neutral, primitive semantic representations, then a system can be built to compare different sets of primitives in order to identify whether these constructs and constraints are identical, slightly different, or totally unrelated. Discrepancies among them can be explicitly specified by the primitive representations and be used in the application development to account for the missing semantics. In this paper, we present a neutral data model ORECOM which has been used in the development of a data model and schema translation system. The model is object-oriented and provides a small number of general structural constructs for representing the structural properties of high-level modeling constructs including those of object-oriented data models. It also provides a powerful knowledge rule specification language for defining those semantic properties not captured by the general structural constructs. The language is calculus-based and allows complex semantic constraints to be defined in terms of triggers and the alternative actions to be taken when some complex data conditions have or have not been satisfied. This paper also presents eight basic constraint types found in many semantically rich data models. These constraint types are represented in the neutral model by parameterized macros and their corresponding micro-rules. Parameterized macros are compact forms of neutral semantic representation which are used in an implemented system for comparing and translating the modeling constructs and constraints of different data models. The corresponding micro-rules are the detailed semantic descriptions of the constraint types. The translation of many modeling constructs and constraints found in several popular models into the neutral representation is illustrated by examples.