Re: dwbp-ISSUE-225: Levels of granularity for dimensions and categories [Quality & Granularity Vocabulary]

I’m finding the treatment of dimensions and measures in the current draft (and in DAQ) confusing. I’m used to thinking of them as two different categories of variables, though the distinction between them is dependent on the analysis one is trying to apply. That is, at least if you use the definition of a measure as a dependent variable and a dimension as an independent one, pretty much any value can be categorized as one or the other. One is not a property of the other. Even when dimensions are defined as categorical variables and measures as quantitative ones, they are still both categories of variables.
-Annette

> On Dec 6, 2015, at 8:36 AM, Data on the Web Best Practices Working Group Issue Tracker <sysbot+tracker@w3.org> wrote:
> 
> dwbp-ISSUE-225: Levels of granularity for dimensions and categories [Quality & Granularity Vocabulary]
> 
> http://www.w3.org/2013/dwbp/track/issues/225
> 
> Raised by: Antoine Isaac
> On product: Quality & Granularity Vocabulary
> 
> Raised in public comment by Werner Bailer
> https://lists.w3.org/Archives/Public/public-dwbp-comments/2015Oct/0019.html
> 
> [
> 2. Dimensions and categories
> 
> The dimensions proposed seem quite high-level, so it is difficult to think of categories that are more general and group dimensions. In contrast, it seems in some cases desirable to have a level between dimensions and metrics. For example, we are dealing with assessing mapping quality. The metrics fall in the dimension of accuracy (i.e., does the output of the mapping process represent the object less accurately), and form a specific group there. To make the distinction of the different levels more confusing, the note in 7.3 Processability currently says "Level on the 5-star scale", which sounds more like a metric than a dimension (there could of course be metrics aggregating results from other metric, daq:requires could be used to express such a dependency). 
> 
> We are not sure if there is a strong need for categories, we would rather propose to consider nesting multiple levels of dimensions to allow grouping.
> ]
> 
> 
>

Received on Monday, 7 December 2015 17:53:09 UTC