JOHN ALIC: Most of what we are talking about here is not really social science R&D. There is no more social science R&D in the services than there is in manufacturing. This is industrial engineering and modeling and simulation; the analogy is factory production systems, just in time logistics management and so on.
CHARLES DUKE: My understanding is that if you guys want to get this straight, you need to go back and get your value chain straight because what you are really saying is that activity at the front end of the value chain -- how big is the market, would this product be successful if offered, etc. -- does not fit your scheme but the response to those market demands is allowable. That is my understanding of what has been said at this meeting.
FRED GAULT: That is certainly consistent with the way in which we capture the data at Statistics Canada.
PARTICIPANT: I want to address the confidentiality issue. In RADIUS we have what we call restricted but unclassified data, and only certain people can get to it. Have you in your collections from industry considered introducing this kind of concept?
PARTICIPANT: I recently retired from the National Center for Health Statistics, a federal statistical agency. What they have been doing and what the Census Bureau has been doing is setting up what they call research data centers, and these allow qualified researchers access to data that are not released for confidentiality reasons. That model is now considered fairly successful..
BILL LONG: It is my understanding that the IRI CIMS database works a little bit like that. No company that contributes data to it can go in and get access to the raw data because then they would have access to competitors’ proprietary data. But almost any academic researcher could get access, subject to restrictions.
BRONWYN HALL: Our thanks to the planning committee and to all of the speakers and participants for their contributions to the discuss ion today. The workshop is adjourned.