Re: dwbp-ACTION-123: Next Step

Hi, Bernadette,

Here, the 3 texts.

Best Regards,
Laufer

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First Text
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<section id="metadata">  <h4>Metadata</h4>
  <p>Data on the web ecosystem has a subjacent architecture   that involves
actors with different roles as, for example,   data Publisher, data
Consumer and data Broker. The Broker   is the one that has information that
can help the Consumer   to find, to access and to process data published by
the   Publisher. Published data is a central entity in this   ecosystem. A
way of helping the Consumer to execute the   tasks listed above is to
provide data about data.   Metadata is data about data. It provides
additional   information about data, to help consumers better understand
the meaning of data, its structure, and to clarify other   issues, as for
example, license of use, the organization   that generated the data, data
quality, data access,   the update schedule of datasets, etc.</p>
  <p>Metadata can be used to help tasks as, for example,   dataset
discovery and reuse. Data consumers could aggregate   metadata about, for
example, data usage, generating feedback   to data providers, in a way of
enhancing the needs of users   and to help improving data quality. Metadata
can be assigned   considering different granularity that goes from a single
property of a resource to a whole dataset, or all datasets   from a
specific organization.</p>
  <p>Metadata can be provided in two forms: human-readable   and
machine-readable. It is important to provide both forms   of metadata in
order to reach humans and applications.   In the case of machine-readable
metadata, the use of standard   vocabularies should be encouraged as a way
of enhancing   common semantics. For example, data provenance could be
described using PROV-O, a W3C Recommendation that provides   a set of
classes, properties, and restrictions that can be   used to represent and
interchange provenance information   generated in different systems and
under different contexts.</p>
  <p>Metadata can be of different types. These types can be classified in
different   taxonomies, with different grouping criterias. For example, a
specific taxonomy could define   three metadata types according to
descriptive, structural and administrative features.   Descriptive metadata
serves to identify a dataset, structural   metadata serves to understand
the format that the dataset is   distributed and administrative metadata
serves to provide   information about version, update schedule, etc. A
different   taxonomy could define metadata types with a scheme according to
tasks   where metadata are used, for example, discovery and reuse.</p>
  <p>Is out of the scope of this document to talk about metadata types  related
to datasets distribution formats, for example, CSV files,   Linked Data,
etc. Each format has its particular metadata scheme   and different W3C
groups are responsible for defining each of   these standards. Taking the
CSV example, W3C CSV on the Web WG   has the mission of providing
technologies whereby data dependent   applications on the Web can provide
higher interoperability when   working with datasets using the CSV
(Comma-Separated Values)   or similar formats.</p>
  <p>In this document we will talk about some types of metadata   that are
common to datasets, independently of the domain or   the distribution
format. A set of these types are described   in the next sections.</p>

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Second Text (suppressed parts)
============================================================
<section id="metadata">
<h4>Metadata</h4>
  <p>Metadata is data about data. It provides additional information  about
data, to help consumers better understand the meaning  of data, its
structure, and to clarify other issues, as for  example, license of use,
the organization that generated  the data, data quality, data access, the
update schedule of  datasets, etc.</p>
  <p>Metadata can be used to help tasks as, for example,  dataset discovery
and reuse, and can  be assigned considering different granularity that
goes  from
a single property of a resource to a whole dataset, or  all datasets from a
specific organization.</p>
  <p>Metadata SHOULD be be available in human-readable  and
machine-readable forms. It is important to provide both forms  of metadata
in order to reach humans and applications. In  the case of machine-readable
metadata, the use of standard  vocabularies should be encouraged as a way
of enhancing  common semantics. For example, data provenance could be
described
using PROV-O, a W3C Recommendation that provides  a set of classes,
properties, and restrictions that can be  used to represent and interchange
provenance information  generated in different systems and under different
contexts.</p>
  <p>Metadata can be of different types. These types can be  classified in
different taxonomies, with different grouping  criterias. For example, a
specific taxonomy could define  three metadata types according to
descriptive, structural  and administrative features. Descriptive metadata
serves to  identify a dataset, structural metadata serves to  understand
the format that the dataset is distributed and  administrative metadata
serves to provide information about  version, update schedule, etc. A
different taxonomy could  define metadata types with a scheme according to
tasks  where metadata are used, for example, discovery and  reuse.</p>
  <p>Is out of the scope of this document to talk about  metadata types
related to dataset distribution formats,  for example, CSV files, Linked
Data, etc. Each format has  its particular metadata scheme and different
W3C groups are  responsible for defining each of these standards. Taking  the
CSV example, W3C CSV on the Web WG has the mission of  providing
technologies whereby data dependent applications  on the Web can provide
higher interoperability when working  with datasets using the CSV
(Comma-Separated Values) or  similar formats. In this document we will talk
about some types of  metadata that are common to datasets, independently of
the  domain or the distribution format.</p>

============================================================
Phil's Text
============================================================
<section id="metadata">  <h4>Metadata</h4>  <p>The data on the Web
ecosystem has an underlying architecture that  involves actors with
different roles. Primary among these are the roles of  data <em>publisher</
em> and data <em>consumer</em> but this suggests a clear boundary  between
the two that may not exist or be helpful. For example, a data <em>broker</em>
would  consume data, process and/or enrich it in some way and then
re-publish it, perhaps  charging a fee for the service.</p>  <p>The data
itself is a central entity in this ecosystem, but on its own it  is likely
to be hard to use if not completely useless. In order to help the consumer
to discover and   understand data sufficiently to be able to use it in some
way requires  more data about the data, that is, metadata.</p>  <p>Metadata
is a complex topic in its own right. It exists at  different levels of
granularity that go from a single property of   a resource to a whole
dataset, or all datasets from a specific organization.  It supports
multiple tasks including dataset discovery and dataset structure.  Data
consumers may aggregate metadata about, for example, data usage,
generating feedback to data providers that might meet more needs of more
users   and to help improve data quality. And it's metadata that describes
the   license and terms of use, the organization that generated the data,
the data quality, the update schedule etc.</p>
 <div class="issue">Should the following 2 paragraphs become best
practices?</div>
  <p>Metadata can be provided in two forms: human-readable and
machine-readable.
It is important to provide both forms of metadata  in order to reach humans
and applications. In the case of  machine-readable metadata, the use of
standard vocabularies should  be encouraged as a way of enhancing common
semantics. For example,  data provenance could be described using PROV-O, a
W3C  Recommendation that provides a set of classes, properties, and
restrictions
that can be used to represent and interchange  provenance information
generated in different systems and under  different contexts.</p>  <p>Metadata
can be of different types. These types can be classified  in different
taxonomies, with different grouping criterias. For  example, a specific
taxonomy could define three metadata types  according to descriptive,
structural and administrative features.  Descriptive metadata serves to
identify a dataset, structural  metadata serves to understand the format
that the dataset is  distributed and administrative metadata serves to
provide  information about version, update schedule, etc. A different  taxonomy
could define metadata types with a scheme according to  tasks where
metadata are used, for example, discovery and reuse.</p>  <p>This document
specifies the intended outcomes for each best  practice and then gives some
guidance on possible implementation methods.  In terms of metadata, the
particular implementation method will depend   on the format of the dataset
distribution, for example, metadata  describing a CSV file should be
provided in a different way than for  an RDF dataset. However, the <em
>intention</em> is the same irrespective  of format.</p>


2014-12-15 14:10 GMT-02:00 Bernadette Farias Lóscio <bfl@cin.ufpe.br>:
>
> Hi Laufer,
>
> Could you please send to me the new version of your text, i.e., the one
> edited by Phil but also without the parts the you suppressed? I'm making
> some updates on the document and I can also update the metadata
> introduction.
>
> Thank you!
> Bernadette
>
> 2014-12-15 12:30 GMT-03:00 Laufer <laufer@globo.com>:
>
>> Hi, All,
>>
>> I wrote the metadata introduction text and, after the comments, I
>> suppressed some parts of the text. Meanwhile, Phil has edited the text (the
>> first one) as a native speaker (thank you Phil), and there was a conflict
>> in github. Now, what we have in the bp document is the first text edited by
>> Phil. I agree with the text but it has parts that I suppressed due to the
>> comments.
>>
>> Bernadette, Phil, I would like to know what is the procedure now.
>>
>> Thank you.
>>
>> Cheers,
>> Laufer
>>
>> --
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>
>
> --
> Bernadette Farias Lóscio
> Centro de Informática
> Universidade Federal de Pernambuco - UFPE, Brazil
>
> ----------------------------------------------------------------------------
>


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