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Re: Nonsemantic Identifiers

From: Adrian Walker <adrianw@snet.net>
Date: Sun, 09 Jul 2006 08:37:46 -0400
Message-Id: <>
To: Alan Rector <rector@cs.man.ac.uk>
Cc: public-semweb-lifesci@w3.org

Alan --

(Also just catching up)

Another advantage of "nonsemantic identifiers" with a (possibly 1:N) 
mapping(s) to "semantic identifiers" is that the former can conveniently be 
structured into different hierarchies and DAGs, to which a mapping can be 
applied as needed to get the English meanings.

A little example [1] of this came up in a taxonomy discussion on another 
list recently.

Just my 2p worth.                -- Adrian

[1]  http://www.reengineeringllc.com/demo_agents/EntertainmentTaxonomy1.agent

Internet Business Logic (R)
Executable open vocabulary English
Online at www.reengineeringllc.com
Shared use is free

Adrian Walker
PO Box 1412
CT 06011-1412 USA

Phone: USA 860 583 9677
Cell:    USA  860 830 2085
Fax:    USA  860 314 1029

At 06:43 PM 7/8/2006 +0200, you wrote:

>Just catching up.
>Could I strongly support the following.  If there is one repeatedly
>confirmed lesson from the medical communities experience with large
>terminologies/ontologies/ it is to separate the "terms" from the
>"entities".  There are always linguistic artefacts, and language
>changes more fluidly in both time and space than the underlying
>entities.   (In medical informatics this is sometimes quaintly
>phrased as using "nonsemantic identifiers").
>On 5 Jul 2006, at 22:43, William Bug wrote:
>>By the way, the "mapping" I refer to above linking instance data
>>where ever it may reside (primary data repositories, pooled/ 
>>analyzed/interpreted data, the scientific literature) to entities
>>in the ontologies requires reference to the lexicon - the TERMS
>>used to describe the ontological fundamentals by the scientists
>>reporting them.  This is true whether an algorithm or a human is
>>trying to understand and interpret a collection of instance data in
>>the context of the relevant knowledge framework, even if that
>>framework resides in the head of the human researcher.
>>I like to think of this distinction as being very coarsely
>>analogous to the distinction between the physical data model in an
>>RDBMS and the many tools used to make that more abstracted,
>>normalized collection of related entities directly useful for
>>specific applications - e.g., SQL SELECT statements, VIEWs, and/or
>>Materialized VIEWS.  Maintaining these as distinct elements goes a
>>long way toward ensuring the abstraction is re-usable for a large
>>set of applications, while simultaneously being able to support
>>each application's detailed requirements through custom de- normalization.
>>This is why I like to keep the lexicon distinct from the ontology.
>>They are intimately linked.  No ontology is free of lexical
>>artifacts (I'm not certain it can or should be), anymore than a
>>lexical graph can be assembled without representing semantic
>>relations.  Analysis of the lexicon can inform how to adapt the
>>semantic graph in the ontology - make it more commensurate with the
>>current state of knowledge as expressed by domain experts, and
>>review of term use in the context of the ontology can be a great
>>help in creating effective, structured, controlled terminological
>>resources.  However, the two types of knowledge resource are
>>constructed via different process, support different Use Cases, and
>>rely on different fundamental relations at their core, however
>>intimately they may be linked.
>Alan Rector
>Professor of Medical Informatics
>School of Computer Science
>University of Manchester
>Manchester M13 9PL, UK
>TEL +44 (0) 161 275 6149/6188
>FAX +44 (0) 161 275 6204
Received on Sunday, 9 July 2006 12:38:31 UTC

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