I consider Jack's question the most important one
yet for practical use of ontologies. (01)
-Rich (02)
Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT EnglishLogicKernel DOT com
9 4 9 \ 5 2 5 - 5 7 1 2 (03)
-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On
Behalf Of Jack Park
Sent: Tuesday, April 02, 2013 10:32 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Ontology for Climate
Change - need input (04)
If it is known to ontologists that common
vocabulary includes the term
"pineapple tree", then is there not a way to
engineer ontologies to
account for such "inaccurate" statements and still
be useful? (05)
Jack (06)
On Tue, Apr 2, 2013 at 8:45 AM, doug foxvog
<doug@xxxxxxxxxx> wrote:
> A lot of general knowledge would be needed in
such an ontology.
> For example, if the system had the information
that pineapples grew at
> the top of stems growing vertically out of the
ground and that such
> stems were disjoint from trees, then it could
reject as inconsistent
> with the knowledge base any statement that
pineapples were found
> growing on trees anywhere.
>
> If the KB also included the information that
many false documents are
> published dated April 1, it should flag as
questionable any claim to
> scientific discoveries made on that date.
>
> Predicates for temperature ranges for growth,
flowering, and fruiting of
> plant species should be in an ontology dealing
with climate change.
>
> Do you have a link to your current ontology?
>
> -- doug foxvog
>
> On Mon, April 1, 2013 13:14, Duane Nickull
wrote:
>> I have been working with a climate group for a
while on creating a top
>> level
>> domain ontology for climate tracking. While we
thought we had everything
>> settled, some surprises came up. In
particular, we found some new
>> evidence
>> that lead us to believe we had missed a major
portion of our model for our
>> ontology pertaining to new proof global warming
was having concrete
>> effects.
>
>> To illustrate the point, consider this
evidence:
>>
http://technoracle.blogspot.ca/2013/04/finally-con
crete-proof-of-global-warm
>> ing.html
>
>
>
>> Any ideas on how to dynamically adjust the
ontology work to compensate for
>> stuff like this?
>>
>> Duane Nickull
>>
>> ***********************************
>> Technoracle Advanced Systems Inc.
>> Consulting and Contracting; Proven Results!
>> i. Neo4J, PDF, Java, LiveCycle ES, Flex, AIR,
CQ5 & Mobile
>> b. http://technoracle.blogspot.com
>> t. @duanenickull
>>
>>
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>>
>> From: Michel Dumontier
<michel.dumontier@xxxxxxxxx>
>> Reply-To: "[ontolog-forum]"
<ontolog-forum@xxxxxxxxxxxxxxxx>
>> Date: Monday, 1 April, 2013 9:12 AM
>> To: "[ontolog-forum]"
<ontolog-forum@xxxxxxxxxxxxxxxx>
>> Subject: Re: [ontolog-forum] Why a data model
does not an ontology make
>>
>>
>>
>>
>> On Sun, Mar 31, 2013 at 9:55 AM, John F Sowa
<sowa@xxxxxxxxxxx> wrote:
>>> Michel, Leo, and Michael,
>>>
>>> JFS
>>>> > But what was produced [by the SW] failed to
address the requirements
>>>> Tim
>>>> > proposed and many others (including Robert
and me) believe are
>>>> essential.
>>>
>>> MD
>>>> > can you list/summarize the requirements and
why you think the steps
>>>> that
>>>> > the semantic web effort has made do *not*
contribute to those
>>>> requirements?
>>>
>>> As I've said repeatedly, three words that Tim
B-L emphasized in the DAML
>>> proposal of 2000 were diversity,
heterogeneity, and interoperability.
>>>
>>> In the final DAML report of 2005, two of them
(diversity and
>>> interoperability) were mentioned just once and
heterogeneity was
>>> never mentioned at all.
>>>
>>> I also believe that Robert Meersman's short
summary is very good:
>>>
>>>
http://starlab.vub.ac.be/website/files/MeersmanBuf
faloAug2007.pdf
>>>> > Why "the" Semantic Web has failed.
>>>> > * Data models vs. ontologies
>>>> > * Legacy systems
>>>> > * Scalability
>>>> > * Methodology
>>>
>>> For point #1, RDF + SPARQL is just YADM -- Yet
Another Data Model.
>>> It has few advantages and many disadvantages
over data models that have
>>> been in use for decades. I have no objection
to YADM if people find it
>>> useful, but I have serious objections to
edicting any single data model
>>> as a requirement for the Semantic Web.
>>
>> So, what we have here is at least some effort
towards standardizing at
>> least
>> one KR format with web standards in mind. RDF
specifies URIs for naming
>> and
>> provides an XML serialization for processing
compatibility. Still, other
>> serializations are available (my preferred is
n-triples), and other
>> vocabularies can build on it (e.g. formal KR
languages like OWL or
>> vocabularies for representation of specific
knowledge e.g. SKOS, PROV,
>> etc).
>> Now that we have RDF(S) + OWL (+OWL profiles),
we see many efforts to
>> align
>> KR languages (e.g. RIF, others) against these -
which I think is highly
>> desired for interoperability.
>>
>>
>>>
>>> For point #2, Tim B-L noted the importance of
interoperability with
>>> legacy systems, but the DAML report ignored
them completely. I can't
>>> blame them for not doing everything in five
years, but they have not
>>> done *anything* to support legacy systems in
the past 13 years.
>>>
>>> And please do not repeat the claim that they
provided a tool to convert
>>> RDBs to RDF. Interoperability means that the
legacy systems work with
>>> the new tools *concurrently* -- not by means
of forced conversion.
>>>
>>
>> ok, how about ontop developed by Mariano
Rodriguez and colleagues:
>> http://ontop.inf.unibz.it/
>> it enables one to map OWL-QL ontologies to SQL
database and answer
>> queries.
>> no conversion required.
>>
>>
>>
>>> For point #3, the SW people claim that OWL is
decidable. That only
>>> means that decisions terminate in *finite*
time -- even though that
>>> time might be greater than the age of the
universe. For anything
>>> the size of the WWW, scalability means no
worse than (N log N) time.
>>>
>>
>> and there have been many projects to deal with
scalability. Consider
>> WebPie
>> (http://www.few.vu.nl/~jui200/webpie.html) by
Frank van Harmelan and
>> colleagues which does RDFS + OWL Horst
reasoning using map reduce.
>>
>>
>>> For point #4, please reread Robert M's slides
for an example of what
>>> a methodology can and should support.
>>>
>>
>> then my point is that the onus is on those that
wish to bring new
>> technology
>> to the masses to go through the standardization
effort where it can be
>> subject to criticism and compromise for real
world deployment.
>>
>> Best,
>>
>> m.
>>
>>
>>
>>> Leo
>>>> > The closest that relational databases get
to having a semantic model
>>>> > is the conceptual schema, which is a type
of conceptual model
>>>> (modeled
>>>> > in a graphic Entity-Relation-Attribute
language, with cardinality
>>>> restrictions).
>>>
>>> Unfortunately, there was never a standard for
a conceptual schema, and
>>> the vendors merely pasted the term 'conceptual
schema' on top of what
>>> they were doing anyway. They turned it into
an advertising slogan.
>>>
>>> E-R-A + cardinality is a requirement that must
be specified in any
>>> conceptual schema (or ontology), but it's far
from sufficient.
>>> And most of the published OWL ontologies do
little or nothing
>>> to go beyond that level.
>>>
>>> From 1978 to 2000, the published R & D on the
conceptual schema and
>>> related issues went far beyond what the
vendors provided, Tim B-L
>>> cited some of that work, but the DAML
developers ignored it.
>>>
>>> Leo
>>>> > Now the above view does have rare
exceptions in the database world:
>>>> e.g.,
>>>> > Matthew West's work immediately springs to
mind. Similarly, HighFleet
>>>> > (formerly Ontology Works) tries to bridge
the ontology-database
>>>> connection.
>>>> > Also, of course deductive databases try to
combine logic programming
>>>> +
>>>> > relational constructs, though these just
focus on the
>>>> implementational
>>>> > apparatus you would need for more
expressive ontologies, but say
>>>> nothing
>>>> > in particular about ontologies.
>>>
>>> I agree that the systems you mention are good.
But there were many
>>> years of very good systems that the SW
ignored. Deductive DBs were
>>> proposed in the 1970s -- note Planner and
Microplanner. RDBs combined
>>> with Prolog and other AI tools have been
widely used since the '80s.
>>> Tim B-L cited them in his DAML proposal of
2000, but the SW gnored them.
>>>
>>> By the way, two commercial companies *based*
on Prolog + RDBs are
>>> Mathematica and Experian. Mathematica started
with Prolog as their
>>> underlying reasoning engine in the '80s, and
they have developed the
>>> foundation into a very rich logic-programming
system that uses RDBs
>>> for external storage.
>>>
>>> Experian uses Prolog + RDBs for Big Data --
much bigger than any
>>> application that uses RDF + OWL. They compute
everybody's credit
>>> rating on a daily basis with every imaginable
input they can find.
>>> They use Prolog so heavily that they bought
the Prologia company.
>>>
>>> MB
>>>> > But I have to add that the transition
between data model and ontology
>>>> > is fluent. In practice, you often have to
make compromises - for
>>>> example to
>>>> > enable better querying or because knowledge
and application data
>>>> cannot be
>>>> > untied easily.
>>>
>>> I agree. And those issues were addressed in
the 3-schema strategy of
>>> of the original ANSI/SPARC TR in 1978. The
conceptual schema -- which
>>> is very close, if not identical, to what we
now call formal ontology --
>>> was at the heart of the proposal. The
physical schema, which is very
>>> close, if not identical to what is called the
data model, specifies
>>> the data formats, layout, and structure. The
application schema
>>> specifies the APIs of the software.
>>>
>>> I also agree that the detailed ontologies will
often use primitives
>>> and operations that have a simple mapping to
the preferred data model.
>>> That is another reason why I have recommended
an underspecified upper
>>> level ontology with families of
"microtheories" for more specialized
>>> ontologies that are optimized for different
kinds of applications.
>>>
>>> But those issues get into details that we have
discussed many
>>> times before, and I won't repeat them now.
>>>
>>> John
>>>
>>>
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>>
>>
>>
>> --
>> Michel Dumontier
>> Associate Professor of Bioinformatics, Carleton
University
>> Chair, W3C Semantic Web for Health Care and the
Life Sciences Interest
>> Group
>> http://dumontierlab.com
>>
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