The subject line is the title of a talk that Robert Meersman presented
at the U. of Buffalo. He discussed some issues that I have emphasized,
but he supports them with a methodology and tools that he and his group
have implemented and used for practical application development. (01)
Following are the slides: (02)
http://starlab.vub.ac.be/website/files/MeersmanBuffaloAug2007.pdf (03)
Following is a related publication: (04)
http://starpc15.vub.ac.be/website/files/sigmod02.pdf
Data modeling vs. ontology engineering (05)
Some quotations from the slides and the paper: (06)
Paper, page 1:
> Unlike data models, the fundamental asset of ontologies is their
> relative independence of particular applications, i.e. an ontology
> consists of relatively generic knowledge that can be reused by
> different kinds of applications/tasks. (07)
Slide 2:
> Why "the" Semantic Web has failed.
> * Data models vs. ontologies
> * Legacy systems
> * Scalability
> * Methodology (08)
Note the scare quotes around "the". Robert (and I) were not opposed
to the basic goals of the Semantic Web, as Tim Berners-Lee presented
them around 2000. On the contrary, we were very hopeful about them.
But what was produced failed to address the requirements Tim proposed
and many others (including Robert and me) believe are essential. (09)
Slide 16:
> Emphasis on methodology
> * Consistent linguistic paradigm
> - Rooted in natural language, not driven by programming agenda
> * Respect for enterprise legacy systems
> - Transform/grow, avoid trauma
> - Handle complexity and scale from day 1
> * Support by flexible DOGMA workbench
> - Specific concept servers (lexons, concept definitions,
> commitments, contexts
> - As late as possible "conceptual binding" of modeling
> primitive instances (010)
DOGMA is the name of the methodology and workbench that Meersman and
his group have developed. I'll avoid endorsing any particular tool,
but I want to emphasize that tools and methodologies along the lines
that Robert and his group have developed are *essential* for bringing
ontologies into mainstream IT. (011)
I would also like to comment on the phrase "rooted in natural language".
Robert gives several examples of how to map a description in NL to
very readable diagrams and how to use them as a basis for ontology
and for application development. (012)
Slides 26 to 30 give some examples in OWL, and later slides show how
to map OWL to the DOGMA diagrams and methodology. (013)
Just for comparison, following is a controlled English statement for
the example shown in slides 26 to 28: (014)
A CS professor is a professor who either teaches a CS course
or belongs to a CS department. (015)
Following is a translation of the sentence to typed first-order logic: (016)
(Forall x:Professor) (CSprofessor(x) iff
((Exists y:CScourse) teaches(x,y))
or ((Exists z:CSdepartment) belongsTo(x,z) ) (017)
I strongly agree with the basic points Robert makes. I believe that
a methodology and a set of tools along the lines he describes would
be extremely valuable for practical ontology development and use. (018)
Note that he presented these slides in 2007 -- six years ago.
The Semantic Web would be far more widely used today if the SW
developers had seriously addressed these issues. Compared to them,
*decidability* is the reddest of red herrings. (019)
John (020)
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