Re: SUO: How to write a rationale for X
John,
This is a good outline. It may take us a while, but I'll try to make a
start on the sections you've suggested.
Adam
At 01:07 PM 7/21/2001 -0400, John F. Sowa wrote:
>At the moment, I do not have a systematic methodology-for-ontology
>article up my sleeve. However, I have recently finished an article
>on semantic networks, which I would cite as an example of how one
>could write a rationale for many related things, including ontologies.
>
>At the end of this note is a note I sent to another list to advertise
>the semantic network article. But in this note, I would like to
>explain how that article illustrates how someone (such as Ian or
>his colleagues) might write the documentation for SUMO.
>
>Following is an analysis of how I wrote that article and how someone
>might apply the approach to other topics, such as SUMO:
>
> 1. The opening section classifies the field of semantic networks
> in six broad categories with a short description of each. For
> SUMO, I would like to see an explanation of the major areas
> to be covered with a brief description of each.
>
> 2. Following that introduction, each of the following sections
> begins with a more detailed definition of the category,
> a historical survey (with citations) of what has been done,
> examples of some of the most typical or influential nets that
> illustrate the features in the definition, and other examples
> that illustrate the range of things that have been done.
> For SUMO, I'd like to see examples taken mainly from the current
> SUMO definitions that illustrate the features in each of the
> broad categories with citations of other approaches, how they
> were used, and how they may have been modified or adapted to
> suit the needs of SUMO, and most importantly, why.
>
> 3. Finally, Section 7 of the article compares network approaches
> to linear notations and gives examples that show how network
> notations can take advantage of the graphic representation to
> express relationships that are harder to express or harder
> to use in a linear notation. For SUMO, I'd like to see some
> explanation of who and what might benefit from SUMO and how and
> why SUMO would help. And the explanation should include some
> specific examples.
>
>Something along the lines I just described would give me much more
>confidence that SUMO is working toward a goal that I should vote
>to support.
>
>John Sowa
>_________________________________________________________________________
>
>I have written an article on semantic networks, which will be published
>in the forthcoming _Encyclopedia of Cognitive Science_:
>
> http://www.macmillanonline.net/Science/ecs.htm
>
>The article may be of interest to CG readers, since it compares
>various network notations, including conceptual graphs, description
>logics, Petri nets, UML, and many others. At the end of this note
>is the opening section. The article itself is on my web site:
>
> http://www.jfsowa.com/pubs/semnet.htm
>
> http://www.jfsowa.com/pubs/semnetw.htm
>
>The first URL uses the official HTML 4.0 symbols, and the second one
>uses the Adobe Symbol font that is usually available on Windows
>machines.
>
>Note: I am in the process of moving my web site to www.jfsowa.com,
>but the old references to bestweb.net will continue to work. For
>the present, I plan to continue using bestweb.net as my email address.
>
>John Sowa
>_________________________________________________________________________
>
> Semantic Networks
>
> John F. Sowa
>
>A semantic network or net is a graphic notation for representing
>knowledge in patterns of interconnected nodes and arcs. Computer
>implementations of semantic networks were first developed for artificial
>intelligence and machine translation, but earlier versions have long
>been used in philosophy, psychology, and linguistics.
>
>What is common to all semantic networks is a declarative graphic
>representation that can be used either to represent knowledge or to
>support automated systems for reasoning about knowledge. Some versions
>are highly informal, but other versions are formally defined systems of
>logic. Following are six of the most common kinds of semantic networks,
>each of which is discussed in detail in one section of this article.
>
> 1. Definitional networks emphasize the subtype or is-a relation between
> a concept type and a newly defined subtype. The resulting network,
> also called a generalization or subsumption hierarchy, supports the
> rule of inheritance for copying properties defined for a supertype
> to all of its subtypes. Since definitions are true by definition,
> the information in these networks is often assumed to be necessarily
> true.
>
> 2. Assertional networks are designed to assert propositions. Unlike
> definitional networks, the information in an assertional network is
> assumed to be contingently true, unless it is explicitly marked with
> a modal operator. Some assertional netwoks have been proposed as
> models of the conceptual structures underlying natural language
> semantics.
>
> 3. Implicational networks use implication as the primary relation
> for connecting nodes. They may be used to represent patterns
> of beliefs, causality, or inferences.
>
> 4. Executable networks include some mechanism, such as marker passing
> or attached procedures, which can perform inferences, pass messages,
> or search for patterns and associations.
>
> 5. Learning networks build or extend their representations by acquiring
> knowledge from examples. The new knowledge may change the old
> network by adding and deleting nodes and arcs or by modifying
> numerical values, called weights, associated with the nodes and
> arcs.
>
> 6. Hybrid networks combine two or more of the previous techniques,
> either in a single network or in separate, but closely interacting
> networks.
>
>Some of the networks have been explicitly designed to implement
>hypotheses about human cognitive mechanisms, while others have been
>designed primarily for computer efficiency. Sometimes, computational
>reasons may lead to the same conclusions as psychological evidence. The
>distinction between definitional and assertional networks, for example,
>has a close parallel to Tulving's (1972) distinction between semantic
>memory and episodic memory.
>
>Network notations and linear notations are both capable of expressing
>equivalent information, but certain representational mechanisms are
>better suited to one form or the other. Since the boundary lines are
>vague, it is impossible to give necessary and sufficient conditions that
>include all semantic networks while excluding other systems that are not
>usually called semantic networks. Section 7 of this article discusses
>the syntactic mechanisms used to express information in network
>notations and compares them to the corresponding mechanisms used in
>linear notations.
Adam Pease
Teknowledge
(650) 424-0500 x571