Versioning

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.