Vagueness

Abstract

In this chapter, we deal with the fact that many aspects of the world are unclear, imprecise or not well defined, and when we try to represent them in a model, we are often confronted with the need to either remove or explicitly manage this vagueness. To this end, we introduce two kinds of vagueness: ontological and epistemic, the first dealing with entities that are naturally imprecise, and the second dealing with the fact that our knowledge about things is not always complete and accurate. To help in dealing with vagueness, we introduce null and unknown semantics. By using the null special keyword in a model, we can state that a fact does not exist; by using the unknown special keyword, we can state that a fact exists, but we are not aware of what it is. Then, we move on to describe some specific techniques to express ontological and epistemic vagueness in conceptual models. We focus on the use of abstract enumerated items (introduced in an earlier chapter), arbitrary time resolution, and the explicit modelling of vague situations through classes and features.