Hi,

A few words from a non-techie.

Quantity means that what is the resulting figure expressing a quantity.
Hb: 8.5 mmol/L

A property of the Hb measurement can be an uncertainty.
This is not an uncertainty of the figure "8.5", but of the Hb  
measurement where 8.5 is the correct resulting number and mmol/L the  
code for the units.
There can be the question that the reported 8.5 really is 8.5 with/ 
without roundoff error.
Only roundoff could be added to DV-QUANTITY as an added extra  
property, I think.

Uncertainty is added information that the uncertainty of the  
measurement is plus or minus something according to a specified (or  
implied) distribution type.
In my view uncertainty is the property of the measurement i.e. the  
specific archetype/template that will express the number
This uncertainty will be expressed in an archetype using attributes  
using DV-QUANTITY expressing the uncertainty as limits and a  
distribution type term (with a default gaussian distribution?)

Gerard Freriks



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On 17-mrt-2006, at 12:42, Thomas Beale wrote:

> The real question is: what is the type & origin of data that need  
> to represented in the more sophisticated way that we are now  
> suggesting? Is it a different category of data? Should be leave the  
> current DV_QUANTITY as is and add a new subtype? Or is it that we  
> should consider a quantity with a 95% T-distribution confidence  
> interval as a pretty normal thing? Should we then start considering  
> the "simple" idea of a symmetric accuracy range (+/- xxx) as really  
> just one specific type of  a confidence interval (it might  
> translate to something like 98% on a normal curve). In other words,  
> should we generalise he "accuracy" notion into a "confidence  
> interval" notion?

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