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Re: Data on the Web scope issue

From: Carlos Iglesias <contact@carlosiglesias.es>
Date: Fri, 14 Feb 2014 12:01:17 +0100
Message-ID: <CAAa1Xzmtf7+hkiwfgJEtVuFaCpzYAxOCfsg3XMuWLGDQ5Pipdg@mail.gmail.com>
To: Makx Dekkers <mail@makxdekkers.com>
Cc: public-dwbp-wg@w3.org
Hi Makx and everyone,

Thanks for starting this interesting discussion.

Another related side-discussion about the scope was the "kind" of data we
should be focusing on. I see current proposals look like quite influenced
by government data envision (e.g. domains, obligations, maybe usage...).
That's not strange because several of us in the group have a strong OGD
background, but I think we should do an extra abstraction effort and try to
avoid focusing exclusively on government data use cases, extending the
scope to data in general.

Also maybe better talk about "motivations" instead "obligations", and I
would never say "fixed" data as every data is usually subject to continuous
updatse and/or modifications (even just for corrections)

Finally, and in relation with the audience topic, I'm wondering whether it
may be worth including another dimension about "potential audience"
(scientist, analysts, tech-people, media, general public, etc) because IMO
this could have a big influence with respect to best practices and how you
should be publishing data.

Best,
 CI.




On 13 February 2014 21:18, Makx Dekkers <mail@makxdekkers.com> wrote:

> Dear all,
>
>
>
> In last week's meeting we had some discussion about the scope of the
> working group. The issue that I brought up was: what do we mean by "data"?
> As far as I understand, the group is not a-priori limited but I think we
> may want to think about distinguishing data in several dimensions.
>
>
>
> Here a set of dimensions we may want to look at, and maybe choose from:
>
>
>
> Domains:
>
> E.g.
>
>          Base registers, e.g. addresses, vehicles, buildings;
>
>          Business information, e.g. patent and trademark information,
> public tender databases;
>
>          Cultural heritage information, e.g. library, museum, archive
> collections;
>
>          Geographic information, e.g. maps, aerial photos, geology;
>
>          Infrastructure information, e.g. electricity grid,
> telecommunications, water supply, garbage collection;
>
>          Legal information, e.g. supranational (e.g. EU) and national
> legislation and treaties, court decisions;
>
>          Meteorological information, e.g. real-time weather information
> and forecasts, climate data and models;
>
>          Political information, e.g. parliamentary proceedings, voting
> records, budget data, election results;
>
>          Social data, e.g. various types of statistics (economic,
> employment, health, population, public administration, social);
>
>          Tourism information, e.g. events, festivals and guided tours;
>
>          Transport information, e.g. information on traffic flows, work
> on roads and public transport.
>
>
>
> Obligation:
>
> E.g.
>
>          Data that must be provided to the public under a legal
> obligation, e.g. legislation, parliamentary and local council proceedings
> (dependent on specific jurisdiction);
>
>          Data that is a (by-)product of the public task, e.g. base
> registers, crime records.
>
>
>
> Usage:
>
> E.g.
>
>          Data that supports democracy and transparency;
>
>          Data that is the basis for services to the public;
>
>          Data that has commercial re-use potential.
>
>
>
> Quality:
>
> E.g.
>
>          Authoritative, clean data, vetted and guaranteed;
>
>          Unverified or dirty data.
>
>
>
> Size (ranging from small CSV files of less than a megabyte to potentially
> tera- or petabytes of sensor or image data)
>
>
>
> Type/format:
>
> E.g.
>
>          Text, e.g. legislation, public announcements, public
> procurement;
>
>          Image, e.g. aerial photos, satellite images;
>
>          Video, e.g. traffic and security cameras;
>
>          Tabular data, e.g. statistics, spending data, sensor data (such
> as traffic, weather, air quality).
>
>
>
> Rate of change:
>
> E.g.
>
>          Fixed data, e.g. laws and regulations, geography, results from
> a particular census or election;
>
>          Low rate of change, e.g. road maps, info on buildings, climate
> data;
>
>          Medium rate of change, e.g. timetables, statistics;
>
>          High rate of change, e.g. real-time traffic flows and airplane
> location, weather data.
>
>
>
> In terms of Best Practices, the last three dimensions (size, type/format
> and rate of change) may require different sets of best practices -
> publishing real-time traffic flow data may require different processes and
> technologies than publishing the results of a census or next year's public
> budget. The other dimensions may not need different best practices but
> maybe they could serve as topics in use cases?
>
>
>
> Makx.
>
>
>
>
>
> Makx Dekkers
>
> makx@makxdekkers.com
>
> +34 639 26 11 46
>
>
>
>
>



Carlos Iglesias.
Data Consultant.
+34 687 917 759
contact@carlosiglesias.es
@carlosiglesias
http://es.linkedin.com/in/carlosiglesiasmoro/en
Received on Friday, 14 February 2014 11:01:46 UTC

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