What is a SUO?

A SUO is something that was talked about quite a bit a year or two ago but seems to be fading a bit of late. SUO stands for "Shared Upper Level Ontology" and represents a baseline of sorts for complex semantic mapping activities. The problem I noticed immediately with the concept was two-fold:

1 - High level taxonomies are extremely useful in situations where an organization (or shared community) has the ability to manage it strictly. For example, there is essentially one shared interpretation of the Animal "Kingdom" originally proposed by Linneaus in the 1700s. However once you move from universal consensus to competing interpretations things start to get complicated. How many official variations of English dialects could be recognized as SUOs and how might they relate to an "Oxford" version?

2 - It is unrealistic to expect that a fairly rich understanding of the potential relationships can be captured within a SUO - which means then it becomes less of a true Ontology and more of a taxonomy. Folks working on on SUOs some years back tried to take this into account:

IEEE SUO working group

Thusfar the largest SUO project is the Suggested Upper Merged Ontology (SUMO) initiative. I'm not too sure how useful this is though as the standard for exchanging the Ontology data is rather narrowly focused (KIF Knowledge Interchange Format). For us to be able to include semantic integration into larger enterprise integration projects a more standard XML-based approach is required.



Copyright 2008, Semantech Inc.

Our Semantic Terminology

As one might expect, the terminology for Semantic Integration is in itself extremely important - it represents our "meta-semantics."

Let’s also explore what these terms signify for us in their enterprise integration
context:

• Vocabulary – This is the atomic level view and is analogous to a data entity.

• Taxonomy – This includes the vocabulary, is a straight forward hierarchy and is analogous to earlier DBMS design paradigms.

• Ontology – This includes both of the above and represents a structure that expresses both a hierarchy and a set of relationships between vocabulary ‘elements’ within that hierarchy. This is roughly analogous to the design paradigms involved in Relational Database technology, although a schema is not necessarily an ontology and tends to be restricted to the system level.

• Semantic Set – This is the recognition that data design (in fact all design) for the enterprise extends beyond the bounds or scope of any one system. The enterprise must deal with multiple ontologies, taxonomies, and vocabularies and reconcile them on an ongoing or evolutionary basis.

Copyright 2008, Semantech Inc.