Re: Versioning

Makx,

Thank you. I think that going deeper into the various meanings of
versioning through additional use cases is a great idea. We can then
discuss those as a group. (This reminds me of the publication patterns
for serial publications - and like those it may be hard to cover every
case.)

One aspect of versioning that may or may not be relevant but that I see
in my field is "updates in place" - that is, databases or datasets in
which updated records are included in the dataset, but there is no
replacement of the entire dataset (although that can usually be
requested). These require a call for "updates since ...", and there may
not be any regularity to the update schedule. These types of datasets
also require three types of updates: new, replace, delete.

Does anyone else have this case, and if so, are you able to create a use
case for it?

Thanks,
kc

On 6/5/17 9:44 AM, Makx Dekkers wrote:
> Apologies for my slow reaction in the discussion today in the call on
> the versioning use case,
> https://www.w3.org/2017/dxwg/wiki/Use_Case_Working_Space#Dataset_Versioning_Information.
> I was struggling with my connection and just managed to note in IRC that
> I didn’t agree with the use case. Disagreeing is not the right word but
> I felt that we maybe need to discuss first what we mean by ‘version’,
> because in my work over the years I have engaged in discussions where
> people didn’t have the same opinion on what we were talking about.
> 
>  
> 
> As I see it, there may be various types of ‘versioning’ relationships
> between datasets. For example:
> 
>  
> 
>   * Evolution: for example, a dataset that is published with
>     year-to-date information; every week or month, new, recent data is
>     appended to the existing data.
>   * Replacement: for example, existing data was wrong in some way, and a
>     new dataset is published that replaces the old data.
>   * Snapshots: for example, continuously changing data like the state of
>     traffic or weather maps with hourly snapshots.
>   * Time series: for example, annual budget data.
>   * Conversion: for example, data that is transformed from one
>     coordinate system to another, or from one set of units to another;
>     similar to translation of textual resources.
>   * Lower/higher granularity: for example, maps in different scales,
>     images in different resolutions, compression like MP3 versus CD
>     sound, and summaries of large amounts of data. 
> 
>  
> 
> In my mind, the use case
> https://www.w3.org/2017/dxwg/wiki/Use_Case_Working_Space#Dataset_Versioning_Information
> is a useful placeholder for a number of more specific cases that might
> have different requirements. I am pretty sure that some of those
> requirements could be satisfied by some explanatory text in the DCAT
> specification; some others might need addition of other properties (or
> even classes?) to DCAT.
> 
>  
> 
> I am planning to write some of this up in separate use cases over the
> next few weeks.
> 
>  
> 
> Makx.
> 
>  
> 
>  
> 

-- 
Karen Coyle
kcoyle@kcoyle.net http://kcoyle.net
m: 1-510-435-8234 (Signal)
skype: kcoylenet/+1-510-984-3600

Received on Monday, 5 June 2017 18:49:54 UTC