Back to Ontology

The three things that are needed for serious Semantic Web applications are a standard set of languages, engines that know how to deal with these languages and knowledge bases in these languages.  This blog is supposed to be about Ontology, that is, Knowledge Representation (KR).  So far, I have had to spend a lot of time on tools and languages. With the testing of engines so far, there is enough of a platform with Pellet, OWL/SWRL/RDF and JENA triplestores to do general Ontology work, so let’s shelve all that for a while.

First of all, the W3C languages (OWL/SWRL/RDF) are not the only language group that can be used for serious Ontology work.

• KIF was created in the 1990′s and had several variants, including SUO-KIF, a version currently in use on the SUMO project.  KIF is logic in a LISP-like syntax and is quite easy to learn and expressive. One thing it lacks is RDF’s partitioning (KIF has a single name space, so the names tend to get long for disambiguation).
• MELD, the language used by CYC and the open source OPEN-CYC (a publically released spin-off project which contains a subset of the full CYC product).  This is another LISP-like language with several extensions to support the special inference capabilities of the CYC engine.
• Common Logic is an upcoming ISO standard language for logic.  Like RDF, it comes in several syntaxes.  Common Logic Interchange Language (CLIF) is a LISP-like syntax (which just proves that computer scientists seriously love their nested parenteses). However, there are other syntaxes such as CGIF (Conceptual Graph Interchange Format), XCL (XML-based notation for Common Logic) and CLCE (Common Logic Controlled English).  The latter is significant, because it represents a trend towards natural controlled languages for specifying logic (also see SBVR and ACE).

For now, I am sticking to OWL/SWRL, but CLCE and others like it are serious enticements.

So, what next? Here are some important areas that look interesting:

• Existing Ontology Standards – There are literally thousands of published standards available on the web.  Take a look at SchemaWeb or Swoogle. There are a few, though, that have been especially well crafted and have gained wide acceptance. These are important because when doing Ontology work, it is better not to start from scratch every time a project starts.
  • Upper Ontologies – These try to be act as universal definitions of everything. Generally, they are abstract and are meant to be the core to which other ontologies (domain-specific) link terms, allowing all the linked into a single world-view and be able to do cross-inference.
  • Domain-specific Ontologies – There are a number of well-accepted standard ontologies for things like various kinds of time, standards, spatial relations and so on.
• Semantic Design Patterns – What is the best approach to representing various kinds of knowledge domains?  While the whole SW effort has been directed almost exclusively at tools and languages, very little work has been done on exactly what and how all this knowledge should be constructed.  Fortunately, philosophers have been arguing these fine points for centuries.  So what approaches are good?  Some areas to examine:
  • Space - There are many ways to represent space (volumes, cartography, grids), ways to measure space (units) and relations in space (topological, compass directions, containment, touching regions, mereology).
  • Time - There are many types of time, measurement systems for time and relations in time.
  • Events (what/where/who and so on) – How to represent things happening sequentially in space and time.
  • Narrative and reification – This covers notions about statements, including who believes them, who said them and in which form, when they were said and whether they are still valid.  This is important in a number of areas, such as understanding narratives and tracking business requirements in systems engineering.
  • Solution Frameworks – If you have knowledge about a problem, how do you arrange the knowledge (“frame the problem”) so that there is a clear way to solve it?  It is amazing how much tacit knowledge is involved in “simple” high-school physics problems in mechanics can be to describe in a logical form.

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