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Re: [ontolog-forum] Ontology for Climate Change - need input

To: <doug@xxxxxxxxxx>, "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Rich Cooper" <rich@xxxxxxxxxxxxxxxxxxxxxx>
Date: Wed, 3 Apr 2013 13:34:09 -0700
Message-id: <7668858A1EE54E6EA503DDA1D1CA8413@Gateway>

In your response, you proposed various interpretations of Jack's questions.  That process - considering a diversity of interpretations simultaneously, is what I consider Jack's question to be about:

    is there not a way to engineer ontologies to account for such "inaccurate" statements and still be useful?

Natural language naturally encompasses diverse interpretations, whether it is written or spoken, read or heard.  Receivers naturally have a choice of multiple interpretations, and whether they use jargon, inference, or probabilistic estimates, they literally have to consider more than a single interpretation to act on when furthering the discourse. 

This process is not rare; it is common in NL.  Choosing among interpretations occurs in every conversation, and there are social NL methods for one party to ask the other questions to help choose among the interpretations that were considered. 

IMHO, Jack asked the question

    "how can we simultaneously handle multiple interpretations with an ontology?"

If you think back to Earley's Algorithm, he suggested a method of parsing that considered multiple parses at each step N in the sentence, and forecast which of those parses were still syntactically acceptable at the N+1st stage.  His algorithm produced all possible parses simultaneously, somewhat like the Link Grammar parser does by solving linguistic constraints. 

Ontology graphs can in principle be traversed in the same multiply forecast ways so that the diversity of feasible interpretations can be continued to the end of the process, finally leaving just those M interpretations which are still feasible when all the processing has been done. 

Personally, I chose the And/Or graph method, with solvability labeling, to be able to represent a plurality of solutions to the graph search problem.  By reading out each feasible solved labeling solution subtree, I can enumerate the interpretations which are still feasible at each step in the search. 

Allowing for simultaneously diverse interpretations like that can let the reasoner choose questions to ask the user which will narrow down the number of possible interpretations, paring away those which the user didn't really intend to convey.  Question answering methods that focus on the feasible interpretations of a user's language and logic can in principle save users time and effort when conveying linguistic information and seeking answers. 

That's why I think Jack's question is so important. 

-Rich

Sincerely,

Rich Cooper

EnglishLogicKernel.com

Rich AT EnglishLogicKernel DOT com

9 4 9 \ 5 2 5 - 5 7 1 2

-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of doug foxvog
Sent: Wednesday, April 03, 2013 12:34 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Ontology for Climate Change - need input

On Tue, April 2, 2013 13:43, Rich Cooper wrote:

> I consider Jack's question

i.e.:

>> 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?

> the most important one yet for practical use of ontologies.

I'm not quite sure what the question meant, so i'm not sure if i agree.

If the term and its meaning(s) is/are known to an ontologist, all that is

needed is to map the NL term to the term(s) in the ontology that

it may represent.  If meanings are known, it is irrelevant to the ontologist

whether any of the meanings may be calculable from the NL term.

It was unclear to me what Jack meant by "inaccurate statements".  If he

meant the term itself not referring to a tree, then i'm not sure that there

is a need for accounting for the term.

If he means determining that some set of statements in the input text

(once it has been faithfully encoded in an ontology language) are

inconsistent, then an inference engine can determine that inconsistency

if it calculates the logical inferences of each statement as it is input

into the inference engine.   It would be best to define a context for the

data source (in this case input article).

If he means that the reason for the inaccurate statement (that it was

an April Fools' joke) should be accounted for, that would require inter-

context reasoning and ontologizing what the concept AprilFoolsJoke means.

If he means that the article should be processed by an NLP and the NLP

should be able to detect that something illogical has been stated, but to

recognize that the illogical thing is a joke instead of backtracking to see

if it can determine a better set of parses, it is an NL question, not an

ontology question.

> -Rich

>

> Sincerely,

> Rich Cooper

> EnglishLogicKernel.com

> Rich AT EnglishLogicKernel DOT com

> 9 4 9 \ 5 2 5 - 5 7 1 2

>

> -----Original Message-----

> From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx On

> Behalf Of Jack Park

> Sent: Tuesday, April 02, 2013 10:32

> 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?

>

> 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-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

>>>

>>>

>>> NOTICE: This e-mail and any attachments may

> contain confidential

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> through its networks for

>>> quality

>>> control purposes.

>>>

>>>

>>>

>>> 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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