Data and What They Refer to

Abstract

In data modeling there is an implicit assumption of a one-to-one correspondence between a data model and the world which the data convey information about. Each data item (value) in the data base corresponds to a property of the world. Our view of the data base reflects our view of the world. For simple situations this is enough, e.g., one data record for each person. For complex situations the simple one-to-one correspondence is no longer enough. When the number of worldly phenomena and the number of data names grow, it becomes increasingly difficult to keep track of how the various concepts relate to each other. Many different views of the world may co-exist, each view serving different purpose and/or different people. No view is more correct than another because each view serves a worthy purpose.

Conceptual data models have been proposed as tools for relating the various world views. For many years research has been conducted in the data base field, in artificial intelligence and information systems to find representions of knowledge that may be easily accepted among users as well as among designers of software and data bases. In spite of the many research efforts we find that various dialects of the ER-model still dominate in the practical world.

For a conceptual model to be successful it should relate well to common sense views of the world, and also relate well to commonly known mathematical formalisms. These are necessary preconditions for being widely accepted. We propose a modeling framework which meets these two conditions. We relate to a common sense view of the world which is based on the old distinctions among ideas, concepts, matter, and images. The mathematical form is elementary discrete mathematics, which in its most simple form is common sense knowledge, even known to children in the elementary school. A visual language for data modeling is supported by a tool which at present consists of an editor and an administrative system for supporting concurrent information systems engineering.