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Re: 15 Ways to Think About Data Quality (Just for a Start)

From: Norman Gray <norman@astro.gla.ac.uk>
Date: Tue, 12 Apr 2011 09:49:25 +0200
Cc: "public-lod@w3.org" <public-lod@w3.org>
Message-Id: <1C97C4EB-AB58-4825-8EEF-CD793E2C32EF@astro.gla.ac.uk>
To: glenn mcdonald <gmcdonald@furia.com>

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 Gray  :  http://nxg.me.uk
Received on Tuesday, 12 April 2011 07:49:51 UTC

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