ontolog-forum
[Top] [All Lists]

Re: [ontolog-forum] Simple Glossary of Data related Terms

To: "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Rich Cooper" <rich@xxxxxxxxxxxxxxxxxxxxxx>
Date: Sat, 4 Jan 2014 15:40:21 -0800
Message-id: <ABD16E53CB6441238417B772D3CEFE68@Gateway>

So if I were to query a dating database for people with the characterization “F”, I would get hermaphrodites as well as the standard female configurations?  And if I were to query for “M”, I would get hermaphrodites that way as well?

 

I think the dating site would like to know F from M, but do hermaphrodites date each other?  Then they would want all members (so to speak) for both the F and M characteristics given that representation. 

 

The point of all this is that context is much more complex than it first seems.  IDEF0 diagrams define a context diagram as all the ICOMAs connected in any way to a given activity.  Each of the ICOMAs would need to be very complex, with structured representations for each ICOMA object.  In my practice, those contexts are what I use to model activities and objects of arbitrarily structured compositions. 

 

But most daily categorizations are very rough, such as M and F, without considering the outliers that are more rare, but important in certain use case contexts. 

 

That is really the point I am making.  LGBTs and hermaphrodites seem to be doing very well without the elaborate categorizations required to furnish all detailed information.  Simpler, closed context diagrams make it much easier to postpone distinctions among category members based on rare situations such as that. 

 

In some email thread from the past few years, there was a discussion on how to characterize rivers.  Examples were brought up that contradicted each and every specification element for a river.  Some have no head source; some evaporate before emptying into other bodies of water, and so on. 

 

The point is that characterization is really a very rough estimate rather than precise logical exclusion and inclusion expressions like we practice with simpler categories. 

 

-Rich

 

Sincerely,

Rich Cooper

EnglishLogicKernel.com

Rich AT EnglishLogicKernel DOT com

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


From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John McClure
Sent: Saturday, January 04, 2014 2:57 PM
To: ontolog-forum@xxxxxxxxxxxxxxxx
Subject: Re: [ontolog-forum] Simple Glossary of Data related Terms

 

hermaphrodite (hɜːˈmæfrəˌdaɪt) n

1. (Biology) biology an individual animal or flower that has both male and female reproductive organs

2. (Medicine) a person having both male and female sexual characteristics and genital tissues


Hermaphoditic is a subclass of male and female classes. The *individual* would be classed as well as lesbian.

On 1/4/2014 2:35 PM, Rich Cooper wrote:

How would you describe a hermaphrodite, who has both male and female appendages, and considers herself female, and lesbian in practice?

 

Adding adjectives to modify classifications just makes the problem more distributed among the properties, and makes programming that representation much harder. 

 

-Rich

 

Sincerely,

Rich Cooper

EnglishLogicKernel.com

Rich AT EnglishLogicKernel DOT com

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


From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John McClure
Sent: Saturday, January 04, 2014 2:27 PM
To: ontolog-forum@xxxxxxxxxxxxxxxx
Subject: Re: [ontolog-forum] Simple Glossary of Data related Terms

 

These values are all expressible as adjectives, meaning that they are not necessarily values for a 'property'.
Any adjective -- any facet -- can be a class, representing Male things, Lesbian things etc.
eg <rdf:type rdf:resource='Male'/>
I believe this is a better _expression_ than <sexualPreference rdf:resource='Male'> which introduces mapping issues.
regards/jmc

On 1/4/2014 12:51 PM, Rich Cooper wrote:

Yes.  For example, the “gender” property values could be M, F, L, G, B, T, and I saw an article the other day about a man who was born with two penises.  Then again, there are hermaphrodites born occasionally. 

 

It’s very difficult to fully understand the entire context around even relatively simple properties that most people don’t bother to think about. 

 

-Rich

 

Sincerely,

Rich Cooper

EnglishLogicKernel.com

Rich AT EnglishLogicKernel DOT com

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


From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Hans Polzer
Sent: Saturday, January 04, 2014 12:26 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Simple Glossary of Data related Terms

 

Kingsley, Rich:

 

I’d suggest adding something in the definition of data that addresses the issue of scope and frames of reference that are usually implicit in the representation of data. The inclusion of the term “big data”  in the glossary and the discussion of boundaries and open-ness underscores this point. Data is about something or a portion of something and not everything, i.e., it has scope – unfortunately not usually explicitly defined. It also has one or more frames of reference in which it is represented, such as character sets, numbering systems, units of measure, naming conventions and namespaces, physical/spatial environmental assumptions, socio-political norms/perspectives, etc., as well as the notion of language already cited in the definition. For example, what are the correct, allowable, values for data elements such as sex, gender, sexual orientation, or political affiliation? I realize this forum doesn’t care much for the notion of context and its scope, but most data I have run across in my career in information systems carries with it all sorts of context and scope assumptions, and interpreting the data properly for whatever purposes someone might have requires an understanding to those context/scope assumptions and how they might relate (or not) to the corresponding assumptions appropriate to the purposes of those seeking/accessing/viewing the data in question.

 

Linked data provides links for one such set of scope/context assumptions, determined by the link creator. But data can be linked in a multiplicity of ways for a multiplicity of purposes – following multiple ontologies and related operational or institutional domains and their respective scope and underlying perspectives, frames of reference, and purposes for representing/amassing data in the first place.

 

Hans

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Kingsley Idehen
Sent: Saturday, January 04, 2014 1:37 PM
To: ontolog-forum@xxxxxxxxxxxxxxxx
Subject: Re: [ontolog-forum] Simple Glossary of Data related Terms

 

On 1/4/14 12:50 PM, Rich Cooper wrote:

Dear Kingsley,

 

The definition you offered for “big data”:

 

“Data that's disparately located, varied in structure, voluminous, and rapidly changing.

 

doesn’t fit what most uses of that word seem to imply.  Businesses maintain big data history files which they mine for discovering knowledge.  But normally, that big data is stored in a data center on the local area network (not on the internet per se) to protect it from outside eyes.  Your definition emphasizes the internet, domains on it having lots of data which can be linked.  Most big data is not really linked – it comes from SQL and NoSQL databases that were captured in the business. 


I am not insinuating that "Big Data" is linked, quite the contrary. My claim is that "Big Data" is a term that refers to:

“Data that's disparately located, varied in structure, voluminous, and rapidly changing.




 

For example, many store chains keep records of how customers visit retail aisles, how much time they spend at each section, and what they finally buy before leaving.  The stores may forward the data to HQ over the internet, but it is protected by encryption, VPNs, etc to keep it from prying eyes.  After it reaches HQ, it is stored and mined.  

 

So my suggestion is to differentiate “Linked Big Data” from the usual “Big Data”.  That way, you can distinguish which kind is being described. 


Yes, which is why I treat "Big Data" as a term that's distinct from "Linked Data", "Linked Open Data", and the "Linked Open Data Cloud" in this document.




-- 
 
Happy New Year,
 
Kingsley Idehen       
Founder & CEO 
OpenLink Software     
Company Web: http://www.openlinksw.com
Personal Weblog: http://www.openlinksw.com/blog/~kidehen
Twitter Profile: https://twitter.com/kidehen
Google+ Profile: https://plus.google.com/+KingsleyIdehen/about
LinkedIn Profile: http://www.linkedin.com/in/kidehen
 
 
 
 



 
_________________________________________________________________
Message Archives: http://ontolog.cim3.net/forum/ontolog-forum/  
Config Subscr: http://ontolog.cim3.net/mailman/listinfo/ontolog-forum/  
Unsubscribe: mailto:ontolog-forum-leave@xxxxxxxxxxxxxxxx
Shared Files: http://ontolog.cim3.net/file/
Community Wiki: http://ontolog.cim3.net/wiki/ 
To join: http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid1J
 

 




 
_________________________________________________________________
Message Archives: http://ontolog.cim3.net/forum/ontolog-forum/  
Config Subscr: http://ontolog.cim3.net/mailman/listinfo/ontolog-forum/  
Unsubscribe: mailto:ontolog-forum-leave@xxxxxxxxxxxxxxxx
Shared Files: http://ontolog.cim3.net/file/
Community Wiki: http://ontolog.cim3.net/wiki/ 
To join: http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid1J
 

 


_________________________________________________________________
Message Archives: http://ontolog.cim3.net/forum/ontolog-forum/  
Config Subscr: http://ontolog.cim3.net/mailman/listinfo/ontolog-forum/  
Unsubscribe: mailto:ontolog-forum-leave@xxxxxxxxxxxxxxxx
Shared Files: http://ontolog.cim3.net/file/
Community Wiki: http://ontolog.cim3.net/wiki/ 
To join: http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid1J    (01)

<Prev in Thread] Current Thread [Next in Thread>