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[ontolog-forum] Data Models v. Ontologies (again)

To: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Barker, Sean (UK)" <sean.barker@xxxxxxxxxxxxxx>
Date: Tue, 20 May 2008 13:16:08 +0100
Message-id: <E18F7C3C090D5D40A854F1D080A84CA4EDAB0F@xxxxxxxxxxxxxxxxxxxxxx>

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of public discussion, any automatically generated statements to the
contrary non-withstanding. It is the opinion of the author, and does not
represent an official company view.    (01)

I'm still trying to sort out when to tell people I'm doing data
modelling and when ontologies, and the following is an interpretation of
some previous postings on the subject.    (02)

A data model assumes a set of entities, and the choice of which entity
to use is implicit, both as natural language text in the data model, and
in the input processes of the system embodying the data model. A data
modeller is primarily concerned with meeting the information
requirements of the system rather than characterising the entities, and
records those aspects (attributes, properties, characteristics) of the
entity of relevance to the functioning of the system.    (03)

An ontology is a formal system of entities (typically a lattice), where
the primary concern of the ontology modeller is to expose the aspects
(characteristics, etc) of the entity which characterise it. Ideally, the
ontology structure can be directly deduced from these characteristics. I
suspect that this is equivalent to saying that an ontology is equivalent
to a decision procedure which classifies things against a lattice
according to its characteristics.(1)    (04)

Characteristics which may be important to a data modeller, such as the
time an entity was added to the system, would not be significant to the
ontologist, since the time the entity is added in no way helps identify
what sort of thing the entity is (where in the lattice it sits).    (05)

That being said, current description techniques (at least those powerful
enough to formally describe an ontology) do not distinguish between
characteristics belonging to a data model and those belonging to an
ontology (as outlined above). This leads to the position that any system
powerful enough to formally describe an ontology is the subject of
ontology research, whether it is used to describe an ontology or a data
model (2).    (06)

>From an engineering viewpoint, I think the distinction is important,
since it must be used to set client expectations. A client who thinks he
has an ontology when what he has got is just a fancy data model is going
to be disappointed when all the wonderful things that ontologies promise
still elude him. Conversely, it would be unethical(3) to sell a client
an expensive ontology when all he needed was a cheap taxonomy.    (07)

---    (08)

(1) The claim that, since there is a real physical world, there must be
a single ontology implicitly assumes that there is only one way to
describe physics - that is, there is a normative metaphysics. The recent
discussion on continuants v. 4-D extensions seemed to be an argument
about metaphysics by proxy, although I don't remember anyone stating the
principles by for preferring one view to another.    (09)

(2) As a description of the scope of academic study, this would make
sense, however ignoring the human factors side of the subject would not
be good engineering.    (010)

(3) Based on the Wolfe recommendations to BAE SYSTEMS on business
ethics.     (011)

Sean Barker
BAE SYSTEMS - Advanced Technology Centre
Bristol, UK
+44(0) 117 302 8184    (012)

BAE Systems (Operations) Limited
Registered Office: Warwick House, PO Box 87, Farnborough Aerospace
Centre, Farnborough, Hants, GU14 6YU, UK
Registered in England & Wales No: 1996687    (013)

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