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Re: [ontolog-forum] What the difference re., Data Dictionary, Ontology,

To: ontolog-forum@xxxxxxxxxxxxxxxx
From: Kingsley Idehen <kidehen@xxxxxxxxxxxxxx>
Date: Sat, 15 Feb 2014 15:03:48 -0500
Message-id: <52FFC824.4000506@xxxxxxxxxxxxxx>
On 2/14/14 8:19 PM, David Eddy wrote:
Kingsley -

On Feb 14, 2014, at 7:47 PM, Kingsley Idehen wrote:

I have spent more than 20+ years of total dedication to making new and emerging technologies work with existing (so called legacy) systems. I founded OpenLink Software to enable integration of data across artificial data silos, created by *myopic* applications. 

But that's the DATA the systems produce.

Systems consume, manipulate, and output data i.e., the manipulate the state of data. Thus, if the data is inaccessible the system doesn't work, or at best it impedes other systems that need to access its data.

I trying to talk about the SYSTEMS, that produce the data.

The SYSTEMS & the DATA are not the same thing.

I have never insinuated that they are. What's the MVC pattern about, for instance? It breaks a system down into constituent parts that deal with: presentation, orchestration, and data representation. That said, nothing stops description of the presentation, orchestration, and data representation using a language that's inherently platform independent.

The SYSTEMS are the machine tools that produce the end product, DATA.

See my comments above, you are misunderstanding me, repeatedly, and simply refusing to accept this fact.

I am reminded of wisdom from the 1840s when industrial America was learning how to make things.  It was noticed that building quality into the manufacturing process is far more efficient than inspecting defects out.

Fine, but I don't see how this point is relevant i.e., there's no new insight in the comment above, from my vantage point.

Just handling the data—the manufactured product—is an exercise in futility until a firm understanding of the upstream manufacturing process is fully understood.

If one doesn't know which systems, programs, logic, data structures & rules are producing the data, how will one know when the data suddenly changes?

You are looking at this whole affair from the inside out. I actually look from the outside in, because we have new technologies constantly being introduced in an innovation continuum; as a result, its all about interfacing with existing systems via the data they produce or manipulate. Basically, we work with data at addresses be it a local app. or a Web-scale service.

In a nutshell, its ultimately all about lego-like infrastructure for data access and state orchestration.

The sort of data dictionary product I'm talking of—decidedly not a list of data elements—enables organizations to do impact analysis—what's connected to what—so that we're not constantly repairing down-stream errors.

I am not talking about a "Data Dictionary Product" .
I am talking about how data is defined.

integration of data across artificial data silos,

Integration is not possible with silos.  You mean interoperable.  There's a huge difference.

Integration is possible when one is in command, owns the budget & has a blank sheet of paper, otherwise the only option is interoperability.

The silos are not necessarily artificial. 

An artificial silo is one that (by design) ignores the concept of data fluidity by not adopting relevant open standards.

They were built that way for valid reasons... available skills, limits of technology, budget, vision, deadlines, organizational boundaries, etc.

We are in a continuum, nothing is static. Change is good. Change and adaptation to change are critical success factors.

Silos are a complex reality we're going to have to learn to deal with... as John Sowa points out, these systems are going to be with us for decades.

Again, you are simply failing to understand my point, completely! Of course, you can make a play on the generic term "silo" but in reality I am specifically referring to systems that make their data inaccessible by failing to evolve with the times.

Any DBMS system can implement an open standard for data access circa. 2014.

Understanding language & meaning across Silos would be an extremely useful application for Ontologies if they can be commercialized.

That's what Ontologies do. And this already works. The challenge is getting people to actually look at what's working instead of constructing endless conjecture laden threads .

David Eddy
Babson Park, MA




Kingsley Idehen	      
Founder & CEO 
OpenLink Software     
Company Web: http://www.openlinksw.com
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