On 4/12/11 3:49 AM, Norman Gray wrote:
Glenn and all, greetings.
On 2011 Apr 9, at 03:10, glenn mcdonald wrote:
I don't think data quality is an amorphous, aesthetic, hopelessly subjective
topic. Data "beauty" might be subjective, and the same data may have
different applicability to different tasks, but there are a lot of obvious
and straightforward ways of thinking about the quality of a dataset
independent of the particular preferences of individual beholders. Here are
just some of them:
This is an excellent list. I think only a minority of these qualities could be
scored precisely, but I think all of them could be scored on some
awful-to-excellent scale, so that while they may not be quite objective
metrics, they're at least clearly debatable.
Complete objectivity is probably impossible here -- inevitable in a world where
the concept of 'Rome' means significantly different things to the local
authority, the ancient historian, and the tourist board. But 'solves my
problem well' is a pretty good substitute.
Best wishes,
Norman
Norman,
Great insight!
Glenn: this is why my demos are oriented towards enabling the beholder
disambiguate his/her/its quest via filtering applied to entity types and
other properties. My entire focus in on this very point outlined by
Norman i.e., dealing with it at massive scales. You cannot enforce
anything on the beholder of data. There are many scenarios where
subjectively bad data is extremely good data.
--
Regards,
Kingsley Idehen
President& CEO
OpenLink Software
Web: http://www.openlinksw.com
Weblog: http://www.openlinksw.com/blog/~kidehen
Twitter/Identi.ca: kidehen
