Human models (mental, digital, visual, etc.) of the geographic environment are necessarily imperfect. While the mathematical principle of homomorphism (often operationalized as fitness for use) allows for imperfect data to be useful as long as they yield results adequate for the use for which they are intended, imperfections are frequently problematic. Although terminology still varies, two types of imperfection are generally accepted: vagueness (a.k.a. fuzziness, imprecision, and indeterminacy), which is generally caused by human simplification of a complex, dynamic, ambiguous, subjective world; and uncertainty (or ambiguity), generally the result of imperfect measurement processes (as discussed in Knowledge Area GD Geospatial Data). Both of these can be manifested in all forms of geographic information, including space, time, attribute, categories, and even existence. Imperfection is also dealt with in Units GD6 Data quality (in the context of measurement), GC8 Uncertainty and GC9 Fuzzy sets (for the handling and propagation of imperfections), and CV4 Graphic representation techniques (in the context of visualization).