In November of 2011, Dan Brickley writes:
How can we package, manage, mix and merge graph datasets that come from different contexts, without getting our data into a terrible mess?
During the last W3C RDF Working Group meeting, we were discussing approaches to packaging up ‘graphs’ of data into useful chunks that can be organized and combined. A related question, one always lurking in the background, was also discussed: how do we deal with data that goes out of date? Sometimes it is better to talk about events rather than changeable characteristics of something. So you might know my date of birth, and that is useful forever; with a bit of math and knowledge of today’s date, you can figure out my current age, whenever needed. So ‘date of birth’ on this measure has an attractive characteristic that isn’t shared by ‘age in years’.
At any point in time, I have at most one ‘age in years’ property; however, you can take two descriptions of me that were at some time true, and merge them to form a messy, self-contradictory description. With this in mind, how far should we be advocating that people model using time-invariant idioms, versus working on better packaging for our data so it is clearer when it was supposed to be true, or which parts might be more volatile?
Interesting to read as an issue for RDF modeling.
Not difficult to solve using scopes on associations in a topic map.
Question: What difficulties do time-invariant idioms introduce for modeling? What difficulties do non-time-invariant idioms introduce for processing?*
Different concerns and it isn’t enough to have an answer to a modeling issue without understanding the implications of the answer.
*Hint: As I read the post, it assumes a shared, “objective” notion of time. Perhaps works for the cartoon world, but what about elsewhere?