07/10/2016 at 15:17 #5888
I have few questions on the definition of Data group.
The definition as described in Measurement Manual 4.01 states that it is a distinct, non empty, non ordered set of data attributes where each included data attribute describes a complementary aspect of the same one object of interest.
What is meant by “Non-ordered” in this definition? Can we have some more explanation on this part along with some examples on “Ordered” and “Non-ordered” set of data attributes?
Additionally, earlier i.e. in Measurement manual 4.0, we had “Non-redundant” in the definition. May I know if this is still applicable in the current version?
Thanks in advance.
09/10/2016 at 13:26 #5890
Hallo Sameer, I must admit we had a tendency to make definitions more complicated or academic than necessary. Over time we are simplifying them.
From the original definition of a ‘Data Group’, we first eliminated ‘non-redundant’. It does not matter for COSMIC sizing if the data group contains redundant data attributes, as long as they all describe the same one object of interest, so including ‘non-reduntant’ in the definition was unnecessary
In v4.0.1, we still say that the data group must be ‘non-empty’ (i.e. there must be at least one data attribute) and that the data elements must be ‘non-ordered’. The latter term means that it does not matter for COSMIC sizing in which sequence the attirbutes occur in the group. A consequence is that you cannot claim that two data groups comprising the same attributes are different just because their sequence in the group is different. I don’t think this is likely to happen in practice, but we try to prevent malpractice or mistakes.
Quite recently in Method Update Bulletin 13, we published a new Note to the definition of a data group to prevent further misunderstandings. I hope it is self-explanatory.
“NOTE: A ‘data group’ does not necessarily mean ‘the set of all data attributes that describe a single object of interest’. The FUR of a piece of software may specify data groups to be formed from any combinations of data attributes that all describe the same object of interest, as needed by different functional processes.”
I hoipe this is all OK
10/10/2016 at 10:32 #5891
Thank you Charles ! This helps.
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