Re: Use machine-readable standardized data formats / Use non-proprietary data formats

Hi Makx, Tomas,

I dont know what exactly was the meaning of the word dirty used by Tomas.

Maybe dirty in the sense that it not follows our BPs and not dirty in the
sense that is not correct. Any data could be incorrect.

I do not think is our job to talk about the data itself. We have a BP that
talks about provenance and we are developing the DQV in a way to try to
provide metadata to help the data consumer to better evaluate and trust the
data she consumes.

The term webby data used by Erik is interesting and maybe we could extend
his list of features and relate our BPs to these features.

Again, I think that a mature model and roadmaps (and now Erik's webby data
list) could help the audience of our documents to better understand why we
are proposing these practices as BPs for publishing data on the web.

All the best,

Em sábado, 15 de agosto de 2015, Makx Dekkers <>

> Tomas,
> >
> > * Dirty data: if the data is available only in a very dirty and
> unfriendly
> format,
> > make it also available: dirty data is better than not data.
> >
> This is not always true. Errors in legislation, medical information, road
> maps can cost lives.
> Of course, if the 'users' are people that make a living or hobby out of
> finding and correcting errors, dirty data is fine, and those users can help
> cleaning it. If on the other hand the users are unsuspecting citizens who
> rely on the data, dirty data is worse than no data.
> In many places, there are laws that oblige the government, pharmaceutical
> companies, food manufacturers etc. to publish data that is correct; if they
> knowingly publish dirty data, they are breaking the law.
> Makx.

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Received on Saturday, 15 August 2015 11:13:52 UTC