On Tue, April 2, 2013 13:31, Jack Park wrote:
> 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? (01)
Inaccurate *statements* or inaccurate *NL terms*? NL rules can
handle standard ways words are put together, even inaccurately.
This could be handled as metaphor. The problem was an intent to
convey a falsehood. (02)
If the ontology has a mapping from "pineapple tree" to PineapplePlant,
then there is no problem with understanding the statement. (03)
A problem might show up if the term "pineapple tree" is *not* mapped
to a term in the ontology & generic NL rules kick in. Such a rule would
posit an instance of Tree-ThePlant, and attempt to state that the specified
pineapple was a fruit of that plant. An appropriate reasoner would reject
this because a pineapple is a fruit of a PineapplePlant and PineapplePlant
is disjoint from tree: (04)
in mt: BotanyMt:
(genls PineapplePlant Plant-NonWoody)
(genls Tree-ThePlant Plant-Woody)
(disjointWith Plant-NonWoody Plant-Woody)
(genls PalmTree Tree-ThePlant) (05)
So other definitions of "tree" would be attempted. If a broader one
fit ("a tree-like bush or shrub", or "anything resembling a tree as in
having a stem and branches"), then a mapping of "tree" to Plant or
(SubcollectionOfWithRelationFromFn SpatialThing shapedLike Tree-ThePlant). (06)
Any ontology that has mapping for NL terms, would not just have an
indication that something was a term, but would have a mapping from
the NL term to one or more terms in the ontology. (07)
So both "pineapple" and "pineapple tree" would have such mappings.
in mt: EnglishMt:
(denotation Pineapple-TheWord
CountNoun 1 (FruitFn PineapplePlant))
(denotation Pineapple-TheWord
MassNoun 1 (StuffFn (FruitFn PineapplePlant))
(denotation Pineapple-TheWord
CountNoun 2 MkII-FragmentationGrenade)
(multiWordString "pineapple" Plant-TheWord
CountNoun 1 PineapplePlant)
(scientificName PineapplePlant "Ananas comosus") (08)
in mt: IdiomaticEnglishMt:
(multiWordString "pineapple" Tree-TheWord
CountNoun 1 PineapplePlant) (09)
The problem would come with NL (010)
> Jack
>
> 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-concrete-proof-of-global-warming.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/MeersmanBuffaloAug2007.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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