Conceptual graphs as a framework for deductive object-oriented databases

Abstract

The idea of deductive object-oriented databases (DOODBs) is to combine the concepts of deductive databases (DDBs) and object-oriented databases (OODBs) into a single database system in order to gain the advantages offered by each of them. This kind of databases is suitable for knowledge bases and many advanced database applications. The formalism of conceptual graphs (CGs), a knowledge representation scheme in AI, is equipped with some useful constructs that are suitable for the requirements of DOODBs. A groundwork for DOODBs based on conceptual graphs has been carried out in this research. The DOODBs are characterized by data abstraction through objects, object identifiers, object types, type hierarchy, property inheritance, methods and message passing and a logical formalism with a sound inference system. Some restrictions and extensions are proposed for the general conceptual graphs so that they can be used to represent the DOODB concepts. These extended conceptual graphs are called deductive object-oriented conceptual graphs (DOOCGs). The object types, individual objects and object identifiers of DOODBs map into concept types, individual CGs and individual referents, respectively. Methods are defined using conceptual schema graphs with bound actors and interpreted in a success/failure paradigm. A set of extended derived rules of inference has been formulated for DOOCGs which are proved to be sound.