Order & meaning in a proposition

Without having read the entire book, there still seems to be an aspect missing that is integral to understanding data -- language. When taking a proposition and normalizing it for the purpose of modeling it, there are times when information is inadvertently lost or left behind because it is not critical. Sample proposition:

Pat is the host who seated the President and the Secretary of the Interior

If we have a relational model for this proposition, we will end up splitting this proposition up and will undoubtedly lose the order of those who were seated. If Pat seated others too, we will also lose the fact that these two seemed to have been seated together or in close proximity of time or place. There is nothing explicit about the ordering, nor is it considered important, perhaps, for our software application. However, there is an ordering here that is not arbitrary -- the President was listed first as an indication of the relative importance of the two who were seated. Even if Pat seated the Secretary of State later, it is likely relevant that such information is in a separate proposition from the one above.

Once we split apart a proposition in such a way that we cannot get the original proposition back, even if we THINK we are getting the important aspects of it back, we have lost some of the meaning we intended to capture.

This is an off-the-top-of-my-head example of where one might lose information when normalizing data and likely not a very good example compared to what might be lost in a typical business application. However, the point is that the process of normalizing data makes it sometimes impossible to retrieve the original propositions, thereby losing some information.

A data modeling process that respects the integrity of the stored propositions so that they can be retrieved again has something going for it that the relational model lacks, it seems. Any thoughts? Thanks. --dawn Received on Tue Apr 06 2004 - 02:02:30 CEST