Late 2008 I mentioned the forthcoming invited book chapter  I wrote for “Novel Developments in Granular Computing: Applications for Advanced Human Reasoning and Soft Computation”, edited by JingTao Yao. Finally, it has been published.
The topics of the book focus on modelling with/representation of granularity, rough sets and logic, data mining, classification, and fuzzy aspects; see the preface and abstracts of the 19 chapters. The free sample chapter is an interesting analysis by Yiyu Yao on Human-Inspired Granular Computing (see menu bar on the left of the page). My contribution is in the modelling section: basically, the book chapter is a self-contained version of chapter 2 of my PhD thesis, with some minor additions from chapters 4 and 5; in short:
Multiple different understandings and uses exist of what granularity is and how to implement it, where the former influences success of the latter with regards to storing granular data and using granularity for automated reasoning over the data or information, such as granular querying for information retrieval. We propose a taxonomy of types of granularity and discuss for each leaf type how the entities or instances relate within its granular level and between levels. Such distinctions give guidelines to a modeler to better distinguish between the types of granularity in the design phase and the software developer to improve on implementations of granularity. Moreover, these foundational semantics of granularity provide a basis from which to develop a comprehensive theory of granularity.
Anyone who has published with IGI before knows about the unusual editing policies and their preferred layout; hence, I will upload the latex-ed preprint soon… here is the preprint.
 Keet, C.M. A top-level categorization of types of granularity. In: Novel Developments in Granular Computing: Applications for Advanced Human Reasoning and Soft Computation. JingTao Yao (Ed.). IGI Global. 2010. pp81-117.