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On Types of Concept System

In my previous blog I discussed the existence of different types of concept systems.  I have found these discussed, oddly enough, not in the literature on data modeling, but in the literature on terminology work.  I have not found discussion of concept systems in philosophy, but that might merely reflect my lack of education, reading in, and general knowledge of philosophy.

Before going further into types of concept systems, we need to establish what a concept system is.  Nordterm 8 Guide to Terminology by Heidi Suonuuti (ISBN 952-9794-14-2) states the following:

Concepts are not independent phenomena.  They are always related to other concepts in one way or another, and form concept systems which can vary from fairly simple to extremely complicated.  In terminology work, an analysis of the relations among concepts and an arrangement of them into concept systems, is a prerequisite for the successful drafting of definitions.

This is not a great definition of "concept system" but it is a good start.  The ISO 704 standard from ISO/TC 37/SC 1 tells us the following:

Concepts do not exist as isolated units of knowledge but always in relation to each other. Our thought processes constantly create and refine the relations between concepts, whether these relations are formally acknowledged or not. A set of concepts structured according to the relations among them is said to form a concept system. 

In organizing concepts into a concept system, it is necessary to bear in mind the subject field that gave rise to the concept and to consider the expectations and objectives of the target users. The subject field shall act as the framework within which the concept field, the set of thematically related but unstructured concepts, is established.

ISO 704 also states:

The terminology of a subject field is not an arbitrary collection of terms. The relevant concepts constitute a coherent concept system based on the relations existing between concepts. The unique position of each concept within a system is determined by the intension and the extension.

This is not the place to get into what is meant by a "subject field".  However, it does seem apparent that a concept system is a number of concepts and the relations between them.  This corresponds to what data modelers call a "conceptual data model", but which they should call a "conceptual model".  A conceptual model describes a set of business information as such, without any thought of how it might be stored as data.

A concept system also differs from a single relationship between two or more terms.   Baldwin's Dictionary of Philosophy defines "relation" in logic as follows:

The mutual dependence of two or more subjects upon a common principle, fact, or truth, of such a kind that any assertion regarding one modifies the meaning of the other.  Accordingly, the predicate is true or false of one taken not independently or in isolation, but only in reference, regard, or respect to the other.  

The way in which a concept system differs from a relationship is that a concept system contains many relationships.

So we have some idea of what a concept system is.   What is interesting is that concept systems are not all of different kinds, but are distributed in types.  This idea is found in terminology work, but does not seem to be found in data modeling.  Perhaps this is because data models are oriented to building databases for data storage, and not for describing business information.    

If there are types of concept system, then each type should have its own properties.  Understanding these properties might help us work with concept systems and hence with definitions.   Data modelers do not seem to have contributed much if any thought about types of concept systems.  It is true that there are many books on data model patterns, but these are oriented to data modeling goals such as not needing to change a database structure unless it is unavoidable.

A challenge will therefore be to catalog the different types of concept system, and their special properties, and find ways to apply them in the practical work of definition management.
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