Re: Mapping between different knowledge sources

Another group that is active in both evaluation of ontologies and ontology
translation issues is in U. Madrid, see [1] for example.

However, a lot of this work is coming from the knowledge representation
perspective and the modeling of complex natural systems, for example in
bioinformatics. To me, a lot of semantic web applications will be in artificial
domains of the sort where tools like UML and ER modeling get applied. In that
case there is quite a bit of evidence that schema translation is possible and a
substantial body of work on semi-automatic identification of the correspondences
between such schemas. See the review at [2] for example.

I'd guess that the Simile ontology translation problems are likely to fall into
two groups. Firstly, there are the sorts of structure mapping problems found in
the database world of [2]. Second, there is the issue of mapping between
Thesaurus terms that arises in the digital library field. For the latter there
has been some work, e.g. MetaNet [3], and is an important work package in SWAD-E
project [4] (Rutherford-Appleton laboratory) which we are also involved in.

Dave

[1] Asunción Gómez-Pérez, "Evaluation of Ontologies", Int J. Intelligent
Systems, 2001

[2] Erhard Rahm and Philip A. Bernstein, "A survey of approaches to automatic
schema matching", VLDB Journal: Very Large Data Bases, 10(4), 2001.

[3] http://jodi.ecs.soton.ac.uk/Articles/v01/i08/Hunter/

[4] http://www.w3.org/2001/sw/Europe/plan/workpackages/live/esw-wp-8.html

"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/

Received on Tuesday, 25 March 2003 05:31:01 UTC