Journal paper on granular perspectives

My paper “The granular perspective as semantically enriched granulation hierarchy” [1] has been accepted in the International Journal Granular Computing, Rough Sets and Intelligent Systems, which is an invited extended version of the GrC’09 paper.

Although the paper is rather logic-based and full of definitions, propositions, and proofs, the underlying idea is quite straightforward. One granulates data and information in multiple ways to generate (granulation) hierarchies that have levels containing more or less detail about one’s domain of interest. Such hierarchies can be as simple as a partonomy of, say, all parts of the human structural anatomy in medicine (cell, organ, body, etc,) or administrative boundaries in GIS (city, province, etc.).  However, what the characteristics of such hierarchies are and what consequences they have on levels of granularity is left implicit throughout literature on granularity. Being imprecise about them easily can yield nonsensical hierarchies using different criteria to granulate information at different levels of detail, which is undesirable in general and in particular for software implementations, whereas having a way to declare that knowledge explicitly gives new opportunities for computation. For instance, to query at ones desired level of detail instead of perpetual time-consuming browsing or simplifying generating partial views of an ontology suited to the context of the domain expert.

The paper describes a way how to represent that hitherto implicit information and to do that in a structured and consistent manner throughout, and justifies why it makes sense to include exactly those properties of the hierarchies. Such a ‘dressed up’ hierarchy I call a granular perspective. Granular perspectives can be uniquely identified, hence, distinguished, by means of formally representing their semantics using a granulation criterion—by what attributes or properties do you divide up things—and type of granularity—how do you divide it—used for granulation. For instance, a criterion could be human structural anatomy (cf., say, functional, or by processes in the human body) and as mechanism using one specific type of relation between the entities in the different levels, e.g., by parthood (cf., say, by subsumption).

Those perspectives can be connected to each other consistently, which can be done by a simple relation or using mereological relations, thereby facilitating cross-granular querying and other reasoning scenarios. (Nothing of that is implemented though—it’s good to [try to] have the theory sorted out first.)

There are some copyright restrictions on the paper that is in print at the moment, so if you want to have a copy, feel free to contact me. An earlier, non-self-standing, version with more ontological analysis can be found in two sections of Chapter 3 of my PhD thesis [2]. To my pleasant surprise, Vogt has, independently, applied my theory of granularity—including the perspectives and linking them—in an informal way with biological material entities [3], which some readers of this blog might find more motivational to start reading than the technical details and, admittedly, fairly simple examples I have used to illustrate it in the thesis. Several illustrations from the eco/GIS domain are described elsewhere [4].


[1] Keet, C.M. (2011). The granular perspective as semantically enriched granulation hierarchy. Int. J. Granular Computing, Rough Sets and Intelligent Systems, (in print).

[2] Keet, C.M. A formal theory of granularity. PhD Thesis, KRDB Research Centre, Faculty of Computer Science, Free University of Bozen-Bolzano, Italy. 2008.

[3] Vogt, L. Spatio-structural granularity of biological material entities. BMC Bioinformatics, 2010, 11:289.

[4] Keet, C.M. Structuring GIS information with types of granularity: a case study. VI International Conference on Geomatics (Geomatics’09), 10-12 February 2009, Havana, Cuba.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.