On Feb 15, 2014, at 3:03 PM, Kingsley Idehen wrote:
What's the MVC pattern about, for instance? It breaks a system down into constituent parts that deal with: presentation, orchestration, and data representation.
Since you started with a blank sheet of paper, you have had the luxury to follow MVC. A lot of systems do not have those divisions. I didn't encounter it until 1981.
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 have yet to see you present something in the OpenLink/RDF/OWL stack that deals with analyzing systems. Analyzing & presenting the data produced by systems, yes. The systems no.
Maybe I'm just stuck on Jim Hendler's statement that his work (of which I assume your work is a taking advantage) has nothing for legacy systems. Has he changed his position?
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.
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.
So you can just take any useful looking data source & stuff it into those 50B triples & not worry about the quality & consistency of said data? You don't have to do any cleanup?
You are looking at this whole affair from the inside out. I actually look from the outside in,
You're saying that outside in is superior to inside out? I would argue both are necessary.
because we have new technologies constantly being introduced in an innovation continuum;
Best comment I've heard on this... "Big Data? My customers can't handle Little Data."
I am not talking about a "Data Dictionary Product" .
I am talking about how data is defined.
So precisely where are you going to keep & maintain the data definitions?
Just the definition of the data? Ignoring the systems that process/produce the data?
We are in a continuum, nothing is static. Change is good.
Change terrifies a lot of people, particularly when it's expensive & risky.
I just saw a Gartner note taking the position that ERP systems installed—and heavily customized—over the past 15 years are the new legacy systems.
Are you aware Massachusetts attempted to replace its revenue system by customizing a CoTS package & walked away after spending $46M?
Any DBMS system can implement an open standard for data access circa. 2014.
Are you referring to the DBMS engine or the application(s) built with the DBMS?
What's the payback to the business to retrofit a silo to current standards?
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 .
Legacy systems are not conjecture. They're what enable our lives.
How long does it take to install an ontology for a 43 year old legacy system. What would be the value?