Recommended: "Providing Metrics and Automatic Enhancement for Hierarchical Taxonomies"

This January 2013 paper, prepared by scholars of the School of Information Systems and Technology, University of Wollongong (Australia) and Computer Science, University of Murcia (Spain) for INFORMATION PROCESSING & MANAGEMENT, volume 49, issue 1, presents an approach to acquiring "quality metrics" from the very beginning development of a taxonomy.   for some ideas on how you might gather and use metrics for justifying your controlled vocabulary projects.
 
Abstract
 
Taxonomies enable organising information in a human–machine understandable form, but constructing them for reuse and maintainability remains difficult. The paper presents a formal underpinning to provide quality metrics for a taxonomy under development. It proposes a methodology for semi-automatic building of maintainable taxonomies and outlines key features of the knowledge engineering context where the metrics and methodology are most suitable. The strength of the approach presented is that it is applied during the actual construction of the taxonomy. Users provide terms to describe different domain elements, as well as their attributes, and methodology uses metrics to assess the quality of this input. Changes according to given quality constraints are then proposed during the actual development of the taxonomy.