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This suggests that reducing the ambiguity within databases will only partly resolve the ambiguity across databases.
The ambiguity of non-systematic identifiers within databases varied from 0.1 to 15.2 % (median 2.5%%).
Table 4 shows the effect of different types of standardization on reducing the ambiguity of non-systematic identifiers within databases.
First, our findings indicate that some non-systematic identifiers are very ambiguous within databases (e.g., TG, triacylglycerol, ester).
Ambiguity of non-systematic identifiers within databases is generally low, with on average few compounds associated with an ambiguous identifier.
Our results show an ambiguity between 0.1 and 15.2 % (median 2.5%%) within databases, whereas ambiguity between databases ranged from 17.7 to 60.2%% (median 40.3 %).
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The information is distributed within database tables in large textual attributes with a free structure.
All of the information is stored within database tables (Paradox by default) with generic structures.
As expected, the within database KL values are much lower and consistent across datasets suggesting a higher degree of consistency within the data from each set.
The recent integration of the temporal dimension within database modelling methods provides a first step towards the representation of the dynamics of evolving systems.
Experimental descriptions are captured and made available as text within database records, published papers and web site content.
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CEO of Professional Science Editing for Scientists @ prosciediting.com