I've been musing more about the semantics of data modeling lately - or really rather about the fact that data modeling is a form of semantic manipulation. The thing that makes semantics interesting is how semantic structures can be mapped onto other semantic structures. That is, the mapping, or recognition, of structures is really what semantics buys us.
In the case of accounting (sorry, I do tend to fixate on particular applications for months or years at a time), it would be instructive to gather the various data models used in open-source software (well, and open formats such as QIF used for non-open software) and do a kind of line-by-line comparison. A mapping, in fact - a mapping onto the semantic constructs that accountants use to talk about accounting.
That nexus is where semantic programming resides, in potential anyway.
At any rate, comparison of projects in this manner would allow us to identify certain features of accounting data structures that were incorporated into or absent from different models. Description of those variants is also part of modeling, and a full description would permit us to auto-generate data migration tools.
And once you can migrate data back and forth between different representations, well, then you have semantic data management, I guess. Not (semantic data) management, that is, but semantic (data management). You've started to graduate from data to knowledge.
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