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Re: [ontolog-forum] Schema.org is not OWL-based (was Re: Toward Human-Le

To: ontolog-forum@xxxxxxxxxxxxxxxx
Cc: Hassan Aït-Kaci <hak@xxxxxxx>
From: John F Sowa <sowa@xxxxxxxxxxx>
Date: Sun, 27 Apr 2014 23:18:00 -0400
Message-id: <535DC868.1030000@xxxxxxxxxxx>
Simon,    (01)

I did *not* say that Schema.org is OWL-based.  GoodRelations used OWL,
and Schema.org adopted GoodRelations but without all the OWL features.
I used the I term "OWL-level", but I should have been more precise.    (02)

> But note that Schema.org contains a lot OWL-level specifications,
> including the GoodRelations ontologies.  That is the point I was
> making in the following statement    (03)

> Schema.org does not use OWL; in some places it does use some parts of
> rdfs, but not in a way that is easy to reason with.  The data model is
> described here: http://schema.org/docs/datamodel.html    (04)

I agree with that point.  But as I have said many times, OWL hits the
*sour spot* of knowledge representation.  I like Schema.org because it
has a good chance of weaning people *away from* OWL.    (05)

As an example of the kinds of KR tools I would recommend, see the
CEDAR system described below.  I really want to see ontologies and
logic-based systems succeed.  But OWL is a dead-end system.  The
sooner we can provide better tools, the better our chances.    (06)

___________________________________________________________________    (07)

The following excerpt is from http://www.jfsowa.com/logic/sorts.pdf    (08)

More recently, Amir and Aït-Kaci (2013) compared the CEDAR system,
which an order-sorted logic (OSL) uses an OSL for classifying and
querying very large taxonomies, to six OWL-based reasoners:  Fact++,
HermiT, Pellet, TrOWL, RacerPro, and SnoRocket. They compared them
on four taxonomies that ranged in size from 111,559 sorts or classes
(Wikipedia) to 903,617 sorts (NCBI).    (09)

For classification, CEDAR was among the three fastest for all the
taxonomies. On the Wikipedia taxonomy, it was five times faster than
the second best (Fact++). For querying, CEDAR beat all the others by
several orders of magnitude. The query time is the most important,
since a classified CEDAR taxonomy can be saved and reused. CEDAR
also detects cycles in the taxonomy, which are a serious source of
inconsistencies.    (010)

Amir, Samir, & Hassan Aït-Kaci (2013) Fast taxonomic reasoning based
on lattice operations, CEDAR Technical Report No. 3, LIRIS-UFR
d’Informatique. http://cedar.liris.cnrs.fr/papers/ctr3.pdf    (011)

For related issues, see the three slide presentations by Hassan A-K:    (012)

Is it possible to make the Semantic Web a reality?
http://cedar.liris.cnrs.fr/papers/intis.pdf    (013)

Reasoning and the Semantic web,
http://cedar.liris.cnrs.fr/papers/ontoforum.pdf    (014)

Empirical study of high-performance triple stores,
http://cedar.liris.cnrs.fr/papers/Presentation_Cedar-PetaSky-LIP_ENS-Web-Site.pdf    (015)

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