Re: Versioning

Hi Annette and Makx,

I think we (Makx and I) agree that "following" is not a case of versioning.
@Annettte, do you also agree? IMO, this case represents a collection of
datasets that share structure but don't share data.

For the other cases, I think we should consider that a dataset is a version
of another dataset when a new dataset is created based on an existing
dataset, i.e, the two datasets will have some data and/or structure in
common. I think this applies both to superseding and adapting cases
mentioned by Makx. On the other hand, If a dataset is modified without the
creation of a new dataset, then there is no versioning. Does it make sense
for you?

Thanks!
Bernadette



2015-07-27 17:30 GMT-03:00 Annette Greiner <amgreiner@lbl.gov>:

> I think you and Bernadette are defining superseding and modifying
> conversely, but I think both cases call for versioning. I would consider
> the case where a dataset is modified and wholly replaced with the corrected
> one as a case where versioning is needed. I also consider the case where a
> dataset is modified and the older version is still available as a case
> where versioning is needed as well. If you have stored an older version and
> it presents itself as the exact same thing, it should be the exact same
> thing. Otherwise, you could reuse a deprecated version without knowing it.
> -Annette
>
> --
> Annette Greiner
> NERSC Data and Analytics Services
> Lawrence Berkeley National Laboratory
> 510-495-2935
>
> On Jul 27, 2015, at 9:56 AM, Makx Dekkers <mail@makxdekkers.com> wrote:
>
> > Annette,
> >
> > Good point.
> >
> > I was not implying that if data is modified, the old version should
> *never*
> > remain available. Maybe a matter of definition: according to my
> > categorisation, if a publisher modifies data and keeps the old version
> > available (the one that may have errors, partial data, outdated
> > information), it falls in the category of superseding.
> >
> > The definition of modifying is then "updating but not keeping the old
> data
> > available". Sometimes you really want to stop people from accessing and
> > using data that you know is wrong.
> >
> > Makx.
> >
> >
> >
> >> -----Original Message-----
> >> From: Annette Greiner [mailto:amgreiner@lbl.gov]
> >> Sent: 27 July 2015 18:20
> >> To: Laufer <laufer@globo.com>
> >> Cc: Makx Dekkers <mail@makxdekkers.com>; Data on the Web Best
> >> Practices Working Group <public-dwbp-wg@w3.org>
> >> Subject: Re: Versioning
> >>
> >> I agree with most of this, but I think that, except for real-time data,
> >> modifying implies a new version. The question of whether something is
> >> superseded seems to me orthogonal. If we didn't maintain a "latest
> > version"
> >> link for the BP doc, would modifications of it not call for a new
> version?
> >> Limiting versioning to things that are wholly replaced suggests that old
> >> versions should never remain available, which I think is not best
> > practice.
> >> -Annette
> >>
> >> On Jul 27, 2015, at 8:11 AM, Laufer <laufer@globo.com> wrote:
> >>
> >>> Thank you Makx for this text about some relations between datasets.
> >>>
> >>>> Do others agree with limiting versioning to the ‘Superseding’
> category?
> >>>
> >>> I agree.
> >>>
> >>> And I think we should have a text in our document telling readers that
> > this
> >> is our understanding about versioning.
> >>>
> >>> But I have a question: what about the other "meanings"? There will be
> > any
> >> type of BPs for them?
> >>>
> >>> Best Regards,
> >>> Laufer
> >>>
> >>> Em segunda-feira, 27 de julho de 2015, Makx Dekkers
> >> <mail@makxdekkers.com> escreveu:
> >>> Thanks Bernadette,
> >>>
> >>>
> >>>
> >>> Good to know that your perspective is that versioning only refers to
> the
> >> ‘Superseding’ case. I fully agree with your perspective.
> >>>
> >>>
> >>>
> >>> However, you make some statements about the other types of changes
> >> that I don’t agree with.
> >>>
> >>>
> >>>
> >>> 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.
> >> 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 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.
> >>>
> >>>
> >>>
> >>> 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.
> >>>
> >>>
> >>>
> >>> 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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