Hi Folks,
So, you have lots of chunks of data and the chunks are highly interrelated. Over time more chunks are added and those new chunks are easily connected in with the other chunks, i.e., the system expands over time.
Example of highly interrelated chunks of data: You have data about an aircraft in flight: its current location, speed, heading, etc. You have data about the aircraft itself: fuel capacity, max speed, max altitude, cruising speed, date built, model number, etc. You have data from FAA radars tracking the aircraft. You have data about the destination and originating points of the aircraft. You have data about the passengers on the aircraft. And you have many other chunks of relevant data. And, the relationships between all these chunks of data must be captured.
[True or False] The only reasonable way to express an expandable system with lots of chunks of highly interrelated data is with RDF, RDF Schema, and/or OWL. It is not practical to express an expandable system with lots of chunks of highly interrelated data using vanilla XML.
[True or False] When dealing with an expandable system with lots of chunks of highly interrelated data it's not practical to use XML Schema to validate the data.
[True or False] When dealing with an expandable system with lots of chunks of highly interrelated data you must adopt the Semantic Web technologies such as inference engines, triple stores, SPARQL, knowledge bases. And your trading partners will naturally join you in your adoption of the Semantic Web technologies.
[True or False] Nobody has ever implemented an expandable system with lots of chunks of highly interrelated data using vanilla XML and using XML Schema for validation. Or, if they did, it was a complete failure.
/Roger
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