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Re: [ontolog-forum] master data vs. ontologies

To: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
From: Edward Barkmeyer <ebarkmeyer@xxxxxxxxxxxx>
Date: Tue, 17 Feb 2015 17:59:31 +0000
Message-id: <BY1PR11MB0296ED75B9B76067CBBFEF35BC2F0@xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx>

+1  I agree strongly with David. 


Thinking of ontologies as schemas/theories is fine, until you actually want to use the ontology to answer a real-world question.  Then you have to be able to use your ‘ontology’ with instances.  Unlike Database land, where the schema and the population are clearly separated, Knowledge Base reasoning requires you to merge the ‘theory’ with the ‘facts’/’hypotheses’ to get results.  Note also that RDF is essentially about instances; adding theory to it is the function of RDF Schema and OWL.




From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of David Price
Sent: Tuesday, February 17, 2015 5:48 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] master data vs. ontologies


On 17 Feb 2015, at 07:24, Matthew West <dr.matthew.west@xxxxxxxxx> wrote:


Dear John and Tom,

Actually this is not the case:

"Ontologies are about the types themselves, not their instances."

[MW>] An ontology can include both instances and types.


It’s true that ontology languages are more powerful wrt relating types than SQL, however I’d not agree that means the ontologies are not about instances. 


In my experience, ontologies are every bit as much about the instances as database tables. I’ve never seen an enterprise ontology that was not about instances.  Their design is always based on analysis of the kinds of instances that will be created and managed using the ontology, including inference and query over those instances. Otherwise, the ontology is just a pretty picture that does not *do* anything. 


Clearly data about real-world individuals like customers which are instances in both worlds. However, lots of what is considered reference data in an RDBMS will turn out to be classes in an ontology. The obvious example is values in columns named something like “<x>_type” that are almost always subclasses or classifications of the instance the row represents.


As an aside - in the linked data world, the ontology is almost an afterthought. Lots of enterprises are following a slightly-more-disciplined linked data approach, and are restructuring their linked data based on good ontologies and so I’ve seen situations where the same instances are viewed by different users through different ontologies. So again, it’s all about the enterprise finding value in the instances (particularly when we replace “linked” with “big” wrt data).







Matthew West                            

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