Re: Versioning

Hi Makx,

Thanks for your message! Good to know that we have some agreement :) I have
some comments:

>
>
> I do not agree that ‘Following’ creates different ‘states’ of the same
> dataset. To me, this year’s budget is only related to last year’s budget
> because they are both budgets, but they are not versions of the same thing.
>

I agree that they are not versions of the same thing. In this case, these
two datasets (last year's budget and this year's budget) won't be
explicitly related? I think we should find a way to specify this
relationship.

They may have the same granularity (e.g. expressed in thousands of dollars)
> but the structure could be different (e.g. because of organisational or
> regional changes). For me, time series (and spatial series) have nothing to
> do with versioning.
>

I agree that time series (and spatial series) have nothing to do with
versioning. However, I don't agree that the structure could be different.
If the structure is different, then there will be a new version, no?


>
>
> I do also not agree that ‘Adapting’ creates a new state (as in data at a
> particular moment). All adaptations are equally valid and exist in
> parallel. To me, adaptations are almost in the same category as the
> different formats that DCAT groups as Distributions of a Dataset.
>

I agree that all adaptations are equally valid and should exist in
parallel. Maybe, the term "state" is not suitable for this, but the idea is
to show that there is a relation between adaptations and the "original"
dataset.


>
>
> Finally, I do I agree that ‘Modifying’ creates a different state and not a
> new version. In many cases, a publisher might not even bother to keep the
> old file but would just change the dct:modified date in the metadata.
>

good!


Cheers,
Bernadette


>
>
> Do others agree with limiting versioning to the ‘Superseding’ category?
>
>
>
> Makx.
>
>
>
>
>
>
>
> *From:* Bernadette Farias Lóscio [mailto:bfl@cin.ufpe.br]
> *Sent:* 27 July 2015 13:51
> *To:* Makx Dekkers <mail@makxdekkers.com>
> *Cc:* Data on the Web Best Practices Working Group <public-dwbp-wg@w3.org>
> *Subject:* Re: Versioning
>
>
>
> Hi Makx,
>
>
>
> Thanks for bringing this discussion and clarifying those differences. IMO
> this kind of distinction is important. However,  I am not sure if we should
> call "versioning" all types of "updates" that you presented. I created the
> following table to help me to visualize these updates in terms of data (or
> content) changes and structure changes.
>
>
>
>
>
> content change
>
> structure change
>
>
>
> Superseding
>
> yes
>
> yes
>
> new version
>
> Following
>
> yes
>
> no
>
> different spatial/temporal granularity
>
> Modifying
>
> yes
>
> no
>
> the data may have been updated or data may have been added
>
> Adapting
>
> yes
>
> no
>
> content is the same, but in different contexts
>
>
>
> I think that just in the first case (superseding) there will be a new
> version of the dataset. In the other cases, there will be different states
> of the same dataset, where a dataset state means the data in the dataset at
> a particular moment.
>
>
>
> Please, let me know if I understood correct and if these ideas make sense
> to you.
>
>
>
> Cheers,
>
> Bernadette
>
>
>
>
>
>
>
>
>
>
>
> *Superseding:*
>
>
>
> Content and structure might be very different but the publisher wants you
> to use the current resource rather than a resource that preceded it. The
> URL stays the same while the content changes although the broad intention
> of the content stays the same.
>
>
>
> Examples:
>
> •                    Today’s website (or, more general, web resource)
> versus last week’s (Memento);
>
> •                    Latest version link, e.g. latest published draft of
> BP http://www.w3.org/TR/dwbp/.
>
>
>
> *Following:*
>
>
>
> The type of content is the same but it covers a different time period.
> Both the new and the old data remain valid. (NB: spatial series, e.g. the
> same kind of data for different regions, are similar to temporal series in
> many respects.)
>
>
>
> Examples:
>
> •                    Sequences of annual budgets;
>
> •                    Daily meteorological observations;
>
> •                    Periodical census data.
>
>
>
> *Modifying:*
>
>
>
> Content, structure and data points are the same to some extent but the
> data may have been updated or data may have been added.
>
>
>
> Examples:
>
> •             Correcting errors in values of data points, e.g. resulting
> from quality control or user feedback;
>
> •             Adding data points, e.g. if measurements from different
> measuring devices come in at different times but belong together;
>
> •             Updating values, e.g. in a Year-to-date file.
>
>
>
> *Adapting:*
>
>
>
> Content and structure are essentially the same but in different contexts.
>
>
>
> Examples:
>
> •             Translations of text fields or labels;
>
> •             Conversion of co-ordinate system;
>
> •             Conversions of measures, e.g. ºC to ºF, imperial units to SI;
>
> •             Changes in granularity.
>
>
>
> Should we somehow take such distinctions into account or should we lump
> them all together?
>
>
>
>
>
> --
>
> Bernadette Farias Lóscio
> Centro de Informática
> Universidade Federal de Pernambuco - UFPE, Brazil
>
> ----------------------------------------------------------------------------
>



-- 
Bernadette Farias Lóscio
Centro de Informática
Universidade Federal de Pernambuco - UFPE, Brazil
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