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Many sites will have a long list of identical typological definitions repeated many times (one for each radiocarbon date).
Technically this is correct, according to our data model: each typo represents a determination of an individual sample (the one taken for radiocarbon dating) according to our source database. However, this is not apparent to the user and probably just looks messy.
I can see two options:
Stick to the strict interpretation of the data model and improve the view to make it clearer that each typo applies to a different sample, perhaps by generating unique labels for samples where they are not present
The less principled but cleaner option – ditch the duplicates and ensure the there is just one occurrence of each typo determination per site, probably attached to a new dummy sample rather than the radiocarbon samples
The text was updated successfully, but these errors were encountered:
Actually I feel better about option 1, but I can see there's a gap between the data-modelling theory (if someone puts "Neolithic" in a row next to a radiocarbon date, they're implying that sample specifically is Neolithic) versus the reality (they probably didn't mean it that way). I can't make my mind up.
A middle-ground option 3: aggregate typos by context, rather than site? So we can have more than one "Neolithic" attached to Site X, but only if they are associated with different contexts?
Many sites will have a long list of identical typological definitions repeated many times (one for each radiocarbon date).
Technically this is correct, according to our data model: each typo represents a determination of an individual sample (the one taken for radiocarbon dating) according to our source database. However, this is not apparent to the user and probably just looks messy.
I can see two options:
The text was updated successfully, but these errors were encountered: