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CLASSIC is a data model that encourages the description of objects not only in terms of their relations to other known objects, but in terms of a level of intensional structure as well. The CLASSIC language of structured descriptions permits i) partial descriptions of individuals, under an 'open world' assumption, ii) answers to queries either as extensional lists of values or as descriptions that necessarily hold of all possible answers, and iii) an easily extensible schema, which can be accessed uniformly with the data. One of the strengths of the approach is that the same language plays multiple roles in the processes of defining and populating the DB, as well as querying and answering. CLASSIC (for which we have a prototype main-memory implementation) can actively discover new information about objects from several sources: it can recognize new classes under which an object falls based on a description of the object, it can propagate some deductive consequences of DB updates, it has simple procedural recognizers, and it supports a limited form of forward-chaining rules to derive new conclusions about known objects. The kind of language of descriptions and queries presented here provides a new arena for the search for languages that are more expressive than conventional DBMS languages, but for which query processing is still tractable. This space of languages differs from the subsets of predicate calculus hitherto explored by deductive databases.
Borgida et al. (Thu,) studied this question.