Re: Mapping between different knowledge sources

Hi Mark,

Mapping data requires that someone understand both data sources.
Until machines are able to understand the data that they manipulate
I would never trust them to generate conversions without the 
prerequisite thought.

I think the best you can hope for is to provide good tools to
help in the extraction or creation of data relevant to each
user.  In that sense of 'interoperate between multiple vocabularies',
I think we have decades of historical use to fall back on.  (And
millenia of human experience.)

In that case RDF is meant to be a better tool for building those
mappings, primarily because it represents relationships very 
strongly.  But as you can see from the difference in representation
of RDF's two basic statement types, the standard triple statement,
and the four triples that constitute a reified statement none of
which looks like the standard triple, mapping in RDF cannot be
considered automatic IMHO.

Cheers,
-kls

On Mon, Mar 24, 2003 at 12:42:50PM -0000, Butler, Mark wrote:
> Apologies in advance as this is skipping on from the use cases, but it seems
> to me one of the key questions in SIMILE (and the semantic web) is whether
> it is possible to interoperate between multiple vocabularies. Interestingly
> quite a bit of work has been done on this before - as I have mentioned the
> KRAFT project between BT PLC and Liverpool, Aberdeen and Cardiff
> Universities considered this problem.
> http://www.csd.abdn.ac.uk/~apreece/Research/KRAFT.html
> KRAFT stands for Knowledge Re-use and Fusion / Transformation
> 
> This section from "Ontological Structures for Knowledge Sharing" M J R
> Shave, 
> www.csc.liv.ac.uk/~mshave/NRIN+.ps
> <http://www.csc.liv.ac.uk/~mshave/NRIN+.ps
> seems particularly relevant:
> 
> "The specification of mapping functions is clearly a key task in the
> construction of a KRAFT network. Knowledge sources can differ in their
> content (their data and its structure), their paradigm (the modelling
> convention used, such as an object oriented database or a knowledge base),
> their representational language (such as predicate calculus, or frames), and
> their ontology. 
> 
> The resolution of each of these differences presents problems, but
> ontological mapping is in many ways the hardest task, if only because it is
> the least well understood. Considerable attention has been devoted in the
> KRAFT project to identifying and classifying the ways in which differences
> between ontologies can occur, and how such mismatches can be resolved. In
> the simplest cases differences can be caused by synonyms (`client' and
> `customer' often have the same meaning), by homonyms (a `crest' can be a
> badge, or the top of a wave or hill), or by differences in underlying
> assumptions (`pass' and `fail' are familiar concepts but have widely varying
> interpretations). Other mismatches are more complex and less straightforward
> to resolve. 
> 
> Two broad categories of mismatch have been recognised. Conceptualisation
> mismatches result from differences in the categories or data structures
> used. Explication mismatches result from the definitions used, which may
> differ in their terminology, their formulae, or the concepts which they are
> defining. Some examples are: 
> 
> Ontology 1 uses the classes mammals, birds 
> Ontology 2 uses the classes carnivores, herbivores 
> A class conceptualisation mismatch 
> 
> Ontology 1 uses the relation hascomponent 
> Ontology 2 uses the relation ismadeof 
> [eg The pair {house, brick} meets either ontology, but {house,roof} fits
> only the first] 
> A relation conceptualisation mismatch 
> 
> Ontology 1 : ship (X) < seagoing (X) ^ large (X) 
> Ontology 2 : vessel (X) < seagoing (X) ^ large (X) 
> A term explication mismatch 
> 
> Ontology 1 : ship (X) < seagoing (X) ^ large (X) 
> Ontology 2 : vessel (X) < floating (X) ^ big (X) 
> A term and formula explication mismatch 
> 
> Ontology 1 : ship (X) < seagoing (X) ^ large (X) 
> Ontology 2 : whale (X) < seagoing (X) ^ large (X) 
> A concept and term explication mismatch 
> A detailed discussion of these issues can be found in [8]. 
> 
> [8] P R S Visser, D M Jones, T J M Bench-Capon and M J R Shave, "An Analysis
> of Ontology Mistmatches: Heterogeneity versus Interoperability", AAAI Spring
> Symposium of Ontological Engineering, California 1997
> 
> br
> 
> Mark H. Butler, PhD
> Research Scientist                HP Labs Bristol
> mark-h_butler@hp.com
> Internet: http://www-uk.hpl.hp.com/people/marbut/

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Received on Monday, 24 March 2003 11:25:56 UTC