Re: [ontolog-forum] Discussion re reasoning about Time and State with RE

[Frank Guerino <Frank.Guerino@xxxxxxxxx>]

Hi Melvin,

You wrote: "RDF is a description language, and it corresponds to, space. Time is the changing notion, it corresponds to reading and writing and is quite hard to model in RDF alone.”

I’ve found that if you think of Time as an Entity Type, a specific instance in time can then be treated no differently than any other instance of any other Data Type.  In other words, it can be treated as a Node in space.  Unfortunately, there is no way to capture and/or map to continuous time, however, any Instance or Entity of any Data Type can be mapped to specific discrete instances in time, with specific semantic context.  This is really no different than Discrete Signal Theory.  For example:

Time “2014.08.19.22:30.07.52.EST” is related as “The Creation Time” for Data Record Instance “XYZ Version 1”

Time “2014.08.19.23:32.40.01.EST” is related as “The Modification Time” for Data Record Instance “XYZ Version 2”

Time “2014.08.19.23:55.12.11.EST” is related as “The Modification Time” for Data Record Instance “XYZ Version 3”

Data Record Instance “XYZ Version 1” is related as “A Version Of” Data Record “XYZ”

Data Record Instance “XYZ Version 2” is related as “A Version Of” Data Record “XYZ”

Data Record Instance “XYZ Version 3” is related as “A Version Of” Data Record “XYZ”

In this way, you can start to do things like get snapshot views in time of a Graph/Network that allows you to compare any one view of a Graph[Tx] against any other view of a Graph[Ty].  In this way, you can also see a Graph move and change through time (kind of like motion picture cards that show motion when flipped fast enough).  The question becomes, how granular do you really want to make your Graph before data explodes and gets out of hand?

I’ve found that this works well with things that don’t change too often, like trying to track the evolution of an Enterprise (and its Assets).  However, it doesn’t work too well when applied to massive transaction volume situations, like turning Securities Exchange Transactions into Graph representations (e.g. across all Exchanges, for all Securities, of all Security Types, at all Price Ticks, for all Buyers and Sellers, etc.).

My Best,

Frank

--
Frank Guerino, Chairman
The International Foundation for Information Technology (IF4IT)
http://www.if4it.com
1.908.294.5191 (M)

From: Melvin Carvalho <melvincarvalho@xxxxxxxxx>
Reply-To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
Date: Tuesday, August 19, 2014 at 7:31 PM
To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
Subject: Re: [ontolog-forum] Discussion re reasoning about Time and State with REST interfaces

On 20 August 2014 01:17, David Whitten <whitten@xxxxxxxxxx> wrote:

There is an interesting discussion re reasoning about Time and State
with REST interfaces
at this URL:

http://teddziuba.github.io/2014/08/18/the-s-in-rest/


as a teaser, the idea is that just because we get a reference to data
in the form of a URL, there is no guarantee that the data referenced
is unchanging.  The example the article talks about is a product being
sold, and the URL returns the current price.  But accounting systems
(especially when money has been spent) don't want to know the current
price, they want to know the price at the time the product was
purchased. And the tax at that time, etc.

So reasoning about information that is changing with time requires a
way to tie the information to a particular time.  Which requires a lot
of internal information to be externalized so the consumer of the web
service can use the information in the way it needs to be used.

What does the group think?

Funnily enough I was just reading that article.

For this I think of Kant and the a priori forms of sensibility, space, time and causality.

RDF is a description language, and it corresponds to, space.

Time is the changing notion, it corresponds to reading and writing and is quite hard to model in RDF alone.

Logic seems to me to correspond to causality.

In Joyce's Ulysses he changes space into the visible, and time into the audible.  It's almost like time and music are related. 

So given this, I think that ontologies and description frameworks need not worry too much about time / state, it seems to be another layer ...

 

David Whitten
713-870-3834

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