Unfortunately, I can't call in to the telecon on Thursday. (01)
But I'd like make some comments. I'll start with a general comment
about Michael's list of topics: None of them mention successful
applications of ontology to mission-critical applications. (02)
I am not asking for presentations *about* applications. But examples
and use cases *derived from* practical experience are far, far more
valuable than abstract notions of what might be theoretically useful. (03)
I sent a related comment to the IAOA list:
> Suggestion: We should gather a list of *successful* cases or,
> more specifically, *deployed* systems that implement an ontology
> that is in daily use for mission-critical applications.
>
> If we had such a list (with URLs for detailed documentation), we
> could analyze them to determine the criteria that distinguish
> practical applications of ontology from wishful thinking. (04)
This suggestion generated one response (copy below). (05)
I agree with Nicola on many points, but I have some serious concerns
about some assumptions that I believe are unrealistic.
> In the past, I have isolated and discussed such criteria: precision,
> completeness, accuracy. See
>
>
>http://www.slideshare.net/NicolaGuarino1/ontology-quality-ontology-design-patterns-and-competency-questions
> Why Evaluate Ontology Technology? Because it Works! (06)
From Nicola's concluding slide:
> Underspecification: simplicity encourages reusability but risks
> to decrease interoperability. (07)
No! Underspecification is *essential* for interoperability. For
examples, just look at the GoodRelations ontology, which is widely
used and has been adopted for Schema.org by Google, Microsoft, Yahoo,
and Yandex. That ontology defines a set of terms with a bare minimum
of details -- and it *maximizes* interoperability. (08)
Precision with unique models is only possible for two kinds of
theories: (a) very general mathematical theories, and (b) very
specialized applications that cannot be shared with anybody else.
Interoperability requires flexibility, *not* unique models. (09)
Tim Wilson asked
> I would consider from the beginning, starting with picking a platform...
>
> Can I get by with freeware like Protege or do I need the capabilities
> of a Cyc-like application? (010)
Unfortunately, there is no platform for ontology that anybody with
a mission-critical application would consider. (011)
When the most widely used platform was developed by university
students, that is a sign that the technology is very immature.
When a platform (Cyc) can only be used by people with long training
in AI, that is another sign that the technology is very immature. (012)
Matthew West has long experience in industry. He understands the
requirements for application development, maintenance, and use:
> We need to make sure that evaluation is grounded in meeting requirements.
>
> So if we think certain evaluation criteria are important, like say
>reusability,
> we need to identify a requirement such as minimising cost across multiple
>applications (013)
Precision with unique models would destroy flexibility, and it would
make changes, extensions, and revisions impossible. You could not
have multiple applications. (014)
John (015)
-------- Original Message --------
Subject: Re: [iaoa-member] semantics in various architectures
Date: Mon, 10 Dec 2012 18:21:31 -0200
From: Mara Abel
To: [IAOA-member] <iaoa-member@xxxxxxxxxxxxxxxx> (016)
Dear all (017)
I can offer two real examples. (018)
Petroledge and Strataledge systems (http://www.endeeper.com/). Both
are based on ontologies for petroleum geology, although they are quite
different in terms of persistence of ontology and user data, mainly
related to the age of each system (10 years, 2 years). (019)
I have published some papers about the ontology definition, but none
describing how we made the system work with the ontologies. (020)
Abel, M., K. Goldberg e L. F. D. Ros. Ontology-based rock description
and interpretation. In: M. Perrin e J.-F. Rainaud (Ed.). _Knowledge
Driven Earth Modelling. Paris: Editions Technip, v.1, 2012.
Ontology-based rock description and interpretation, p.268-271 (021)
Abel, M., L. S. Mastella, L. a. L. Silva, J. A. Campbell e L. F. D.
Ros. How to model visual knowledge: a study of expertise in
oil-reservoir evaluation. In: F. Galindo, M. Takizawa/, et al/ (Ed.).
_Database and Expert Systems Applications_. Zaragoza , Spain:
Springer-Verlag GmbH & Company KG, Berlin, Germany, v.3180, 2004.
p.455-464. (Lecture Notes in Computer Science) (022)
Mara (023)
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