Re: DQV - metrics related to the completeness dimension

I agree that we can’t create a standard for one interest group. My point is that the DQV can serve many purposes. You may have a use case for not using the vocabulary to assert objective measures. I still don’t see any reason that those with other use cases shouldn’t have the option to use the DQV in ways that it can be meaningful for them.
(And I imagine your audience thought you were asking whether their government could be objective about its assessment of its own data, which is pretty different from whether it might state that a dataset doesn’t contain numbers for a particular province, for example.)
-Annette

--
Annette Greiner
NERSC Data and Analytics Services
Lawrence Berkeley National Laboratory
510-495-2935

On Sep 30, 2015, at 1:27 PM, Steven Adler <adler1@us.ibm.com> wrote:

> Let me rephrase.  We can't create a standard for the best behaviour of one interest group.  We have to create a standard for many interests and behaviours.  
> 
> I'm at the World Bank today participating in a forum on Investing in Sierra Leone Diaspora and I asked my audience if they would ever trust their government to asset their own data quality with objective assertions and they laughed.  That government can't be trusted to keep a decision for more than a week.  
> 
> Best Regards,
> 
> Steve
> 
> 
> 
> Annette Greiner --- Re: DQV - metrics related to the completeness dimension ---
> 
> From:	"Annette Greiner" <amgreiner@lbl.gov>
> To:	"Steven Adler" <adler1@us.ibm.com>
> Cc:	"Nandana Mihindukulasooriya" <nmihindu@fi.upm.es>, "Debattista, Jeremy" <Jeremy.Debattista@iais.fraunhofer.de>, "Data on the Web Best Practices Working Group" <public-dwbp-wg@w3.org>, "Makx Dekkers" <mail@makxdekkers.com>
> Date:	Wed, Sep 30, 2015 3:14 PM
> Subject:	Re: DQV - metrics related to the completeness dimension
> 
> I mean to challenge your assumption that we are not creating the DQV for use by scientists to make statements about the completeness of data sources. I think that is a mistake.
> --
> Annette Greiner
> NERSC Data and Analytics Services
> Lawrence Berkeley National Laboratory
> 510-495-2935
> 
> On Sep 30, 2015, at 11:52 AM, Steven Adler <adler1@us.ibm.com> wrote:
> 
>> Because people don't know what they don't know.  Scientists, politicians, data experts - anyone who published data has limited resources to do so and poor data quality is endemic to publishing.   Sources have to be corroborated and we can make it easier to corroborate by building into the vocabulary.
>> 
>> Best Regards,
>> 
>> Steve
>> 
>> 
>> 
>> Annette Greiner --- Re: DQV - metrics related to the completeness dimension ---
>> 
>> From:	"Annette Greiner" <amgreiner@lbl.gov>
>> To:	"Steven Adler" <adler1@us.ibm.com>
>> Cc:	"Nandana Mihindukulasooriya" <nmihindu@fi.upm.es>, "Debattista, Jeremy" <Jeremy.Debattista@iais.fraunhofer.de>, "Data on the Web Best Practices Working Group" <public-dwbp-wg@w3.org>, "Makx Dekkers" <mail@makxdekkers.com>
>> Date:	Wed, Sep 30, 2015 1:29 PM
>> Subject:	Re: DQV - metrics related to the completeness dimension
>> 
>> Why do you insist on this? My primary interest in this group is on behalf of scientists. I think they would welcome a way to express what they see as the completeness of a dataset to their colleagues. -Annette
> 
>> On Sep 30, 2015, at 6:05 AM, Steven Adler wrote: > I want to say emphatically that we are not dealing with scientists publishing papers and making scientific statements about completeness of data sources. We are talking about organizations with financial interests in asserting their point of view when they publish data. We must insist that one assertion of quality is never enough.