[pc] >> Those who have immediate problems to solve in a short time frame will find this of no direct relevance. But if one needs to communicate **accurately** between systems, the tactic of using a single language in the communication process is unavoidable.
From: ontology-summit-bounces@xxxxxxxxxxxxxxxx [mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Kingsley Idehen
Sent: Saturday, February 08, 2014 7:03 PM
To: ontology-summit@xxxxxxxxxxxxxxxx
Subject: Re: [ontology-summit] Ontology driven Data Integration using owl:equivalentClass relations
On 2/8/14 6:26 PM, Patrick Cassidy wrote:
Kingsley, just a reply to one point:
[PC] >> If one only wants to create equivalencies and use that to perform probabilistic or pattern-matching reasoning,
>> that may lead to useful results that can be helpful for the humans who evaluate the results.
>> But don’t expect the kind of accuracy that would be needed to allow the computers
>> to make mission-critical decisions without human intervention.
>
[KI] > Computers cannot be left alone to mission-critical decisions for humans. What they can
> do is perform a lot of the grunt work that makes humans beings make better decisions, more productively.
Well, getting computers with increasing ability to perform without humans is, I believe one of the goals that motivates many workers with knowledge based systems (including myself), and in other fields as well.
A computer can perform autonomously, with varying degrees of intelligence, while ultimately remaining a productivity tool for human beings. A computer cannot replace a human being in areas where said entity is inherently superior i.e., the realm of cognition.
Computers are emotionless processors of data that for the most part aren't subject to fatigue (although we know disks have finite life spans too).
We hear a lot about self-driving cars,
And there will be a lot of problems with those cars without human participation at some level. Same applies to the drone delivery system that Amazon has been talking about.
or airplane defense systems that respond automatically to perceived threats,
Yes, but there are still productivity tools for humans i.e., letting use apply our minds to the insights they provide.
or billion dollar rovers that have to negotiate uncertain terrain on other planets.
Exploration of Mars is good and productive use of computer technology.
At present such systems need to be carefully constructed for restricted domains, but increased capability will make them more useful, and is eagerly sought after.
Yes, that's all about productivity oriented contributions in my world view.
My own interest is precisely to learn what is required for systems to become as capable as humans in a wide range of situations.
Yes, but those situations will be beneficial when the focal point is dealing with issues that human beings don't handle well. Typical characteristics of such issues include:
1. physically challenging
2. emotionally challenging
3. repetition laden.
Those who have immediate problems to solve in a short time frame will find this of no direct relevance. But if one needs to communicate **accurately** between systems, the tactic of using a single language in the communication process is unavoidable.
Yes, and maybe that language ultimately boils down to First-order logic.
For two or a small number of systems that can agree ahead of time on meanings of terms or data fields, that single language is effected by such prior communication. For the case where one party puts data on the web and another party wants to use the data without prior communication with the first party, the user still needs to understand the meanings of the terms used by the data supplier . . . and if one want accuracy over a range of topics, there is no alternative that I have seen to precise logical descriptions of the terms that both parties have access to. Precise logical descriptions of terms is the function of the foundation ontology, and both communicating parties need to use the same foundation ontology (of which there could be more than one).
[PC] >> Or, if one only wants to extract some one or two properties of an entity (e.g. the director of a film), equating “film” in two different ontologies may work as intended. But extreme caution is advised.
>>
[KI] > Of course this has to be done with caution. I've never perceived ontologies as a mechanism for making computers perform tasks for which they are ill equipped.
> Computers are tools, and when used properly, extremely powerful productivity tools for humans.
Yes, computers are tools and the tasks for which they are properly equipped are becoming increasingly sophisticated. For the task of communication among computer systems that need to properly interpret the transmitted data, some prior agreement on meaning is required, and a common foundation ontology can provide that agreement over a broad range of topics with the least effort. Otherwise one will have probabilistic interpretations that will be suitable for some applications, but too inaccurate for others.
It will always be about "horses for courses" so the key is to work with data representation structures that are flexible, open, and driven by entity relation semantics. We are much closer to that than many assume. This is why I prefer to accompany my views with live demonstrations :-)
Kingsley
Pat
On 2/7/14 3:53 PM, Patrick Cassidy wrote:
There is a serious problem with the suggested methodology:
> Two ontologies or vocabularies (for instance FOAF and Schema.org) include definitions for the same class (or kind) of entity e.g., an Organization,
> and as a consequence we end up with Web accessible documents comprised of RDF statements that describe Organizations as instances of foaf:Organization or schemaorg:Organization.
>
> Challenge: How do we get a merged view of all the organizations, irrespective of how they've been described across various RDF documents?
>
> Solution:
>
> 1. Make a mapping/bridge/meta ontology that uses owl:equivalentClass relations to indicate the fact
> that <http://xmlns.com/foaf/0.1/Organization> and <http://schema.org/Organization> are equivalent.
>
> 2. Load the mapping/bridge/meta ontology document into a data management system that's capable
> of applying reasoning and inference to the equivalence claim based on its comprehension of the relation semantics expressed
>
> 3. Access instances of the <http://xmlns.com/foaf/0.1/Organization> classes (e.g., by seeking a description
> of <http://xmlns.com/foaf/0.1/Organization> which should produce a solution that includes subjects
> of instanceOf (rdf:type) relations) -- and this will show a union of all instances of across <http://xmlns.com/foaf/0.1/Organization> and <http://schema.org/Organization>
>
> 4. Reverse the action in step 4 above -- the results should be the same.
If you create an equivalence mapping between entities in independently developed ontologies and try to “reason” with it in any but the most highly restricted manner, you will almost certainly find unintended inferences, likely logical inconsistency, and potentially a great deal of gibberish. When you look at the logical specifications of entities of the same name in different ontologies, they are often quite different, even though the intuition for the meanings may be similar. For “organization”, for example, some ontologies have that as a subtype of “group of people”. In some legal jurisdictions, an Organization can exist without any members – i.e., no people. That can lead to logical contradictions if different definitions are equated. I have never seen “process” defined the same way in any two independent ontologies.
Yes, but nothing I've outlined contradicts the point you are making.
My point is that you can opt to apply reasoning and inference based on classes (entity types/kinds) described across different ontologies. There is no such thing as one ontology that rules all. What you can do is opt to apply meta/bridge/mapping ontologies, according to your situation.
In my example, I am demonstrating how understanding of FOAF and Schema.org classes can be used to integrate instances of classes from either ontology. Note, I specifically include examples with and without inference & reasoning to drive home the point that is all loosely coupled i.e., its application and use is a choice made by system user.
If one only wants to create equivalencies and use that to perform probabilistic or pattern-matching reasoning, that may lead to useful results that can be helpful for the humans who evaluate the results. But don’t expect the kind of accuracy that would be needed to allow the computers to make mission-critical decisions without human intervention.
Computers cannot be left alone to mission-critical decisions for humans. What they can do is perform a lot of the grunt work that makes humans beings make better decisions, more productively.
Or, if one only wants to extract some one or two properties of an entity (e.g. the director of a film), equating “film” in two different ontologies may work as intended. But extreme caution is advised.
Of course this has to be done with caution. I've never perceived ontologies as a mechanism for making computers perform tasks for which they are ill equipped.
Computers are tools, and when used properly, extremely powerful productivity tools for humans.
Kingsley
Pat
Patrick Cassidy
MICRA Inc.
cassidy@xxxxxxxxx
1-908-561-3416
Kingsley, +1 ... Your mapping/bridge/meta ontology is my "integrating ontology". And, you captured the essence extremely well in your demos.
2. Reasoning with the mappings
Clearly this works over data that is Linked Data or data in ontologies.
On Fri, Feb 7, 2014 at 10:01 AM, Kingsley Idehen <kidehen@xxxxxxxxxxxxxx> wrote:
All,
Starting a new thread based on the theme above to make what I am trying to demonstrate clearer.
Situation:
Schema.org [1] is a collaborative effort aimed as simplifying structured data publication to the Web. As part of this effort, a number of collaborators have collectively produced a number of shared vocabularies under the "schema.org" namespace.
In addition to what's being produced by Schema.org there are a thousands of shared ontologies and vocabularies that have been constructed and published to the Web from a plethora of sources, many of these have been aggregated by services such as LOV (Linked Open Vocabulary) [2] which is basically accentuates the TBox and RBox aspects of the Linked Open Data (LOD) Cloud.
Typical Integration Problem:
Two ontologies or vocabularies (for instance FOAF and Schema.org) include definitions for the same class (or kind) of entity e.g., an Organization, and as a consequence we end up with Web accessible documents comprised of RDF statements that describe Organizations as instances of foaf:Organization or schemaorg:Organization.
Challenge: How do we get a merged view of all the organizations, irrespective of how they've been described across various RDF documents?
Solution:
1. Make a mapping/bridge/meta ontology that uses owl:equivalentClass relations to indicate the fact that <http://xmlns.com/foaf/0.1/Organization> and <http://schema.org/Organization> are equivalent.
2. Load the mapping/bridge/meta ontology document into a data management system that's capable of applying reasoning and inference to the equivalence claim based on its comprehension of the relation semantics expressed
3. Access instances of the <http://xmlns.com/foaf/0.1/Organization> classes (e.g., by seeking a description of <http://xmlns.com/foaf/0.1/Organization> which should produce a solution that includes subjects of instanceOf (rdf:type) relations) -- and this will show a union of all instances of across <http://xmlns.com/foaf/0.1/Organization> and <http://schema.org/Organization>
4. Reverse the action in step 4 above -- the results should be the same.
Live Demo Link:
[1] http://lod.openlinksw.com/describe/?url=""> -- description of <http://xmlns.com/foaf/0.1/Organization> *without inference and reasoning enabled*, so the relations presented are specific to the aforementioned class.
[2] http://lod.openlinksw.com/describe/?url=""> -- description of <http://schema.org/Organization> *without inference and reasoning enabled*, so the relations presented are specific ot the aforementioned class .
[3] http://lod.openlinksw.com/describe/?url=""> -- description of <http://xmlns.com/foaf/0.1/Organization> *with inference and reasoning enabled*.
[4] http://lod.openlinksw.com/describe/?url=""> -- description of <http://schema.org/Organization> with *inference and reasoning enabled*.
--
Regards,
Kingsley Idehen
Founder & CEO
OpenLink Software
Company Web: http://www.openlinksw.com
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