--- a/data-cube-ucr/index.html Fri May 31 08:13:56 2013 +0200
+++ b/data-cube-ucr/index.html Thu Jun 06 10:23:55 2013 +0200
@@ -28,15 +28,14 @@
In this document, the <a href="http://www.w3.org/2011/gld/">W3C
Government Linked Data Working Group</a> presents use cases and lessons
supporting a recommendation of the RDF Data Cube Vocabulary [<cite><a
- href="#ref-QB-2013">QB-2013</a></cite>]. The document describes use cases of
- the data cube vocabulary from existing deployments of and experiences
- with an earlier version of the data cube vocabulary [<cite><a
- href="#ref-QB-2010">QB-2010</a></cite>] as well as other possible use cases
- that would benefit from using the vocabulary. In particular, the
- document identifies benefits and challenges in using a vocabulary for
- representing statistics. Also, it derives lessons that can be used for
- future work on the vocabulary as well as for useful tools
- complementing the vocabulary.
+ href="#ref-QB-2013">QB-2013</a></cite>]. The document describes case studies
+ of existing deployments of an earlier version of the data cube
+ vocabulary [<cite><a href="#ref-QB-2010">QB-2010</a></cite>] as well
+ as other possible use cases that would benefit from using the
+ vocabulary. In particular, the document identifies benefits and
+ challenges in using a vocabulary for representing statistics. Also, it
+ derives lessons that can be used for future work on the vocabulary as
+ well as for useful tools complementing the vocabulary.
</p>
</section>
@@ -70,10 +69,9 @@
<p>The rest of this document is structured as follows. We will
first give a short introduction to modelling statistics. Then, we will
describe use cases that have been derived from existing deployments or
- feedback to the earlier version of the data cube vocabulary. In
+ from feedback to the earlier version of the data cube vocabulary. In
particular, we describe possible benefits and challenges of use cases.
- Afterwards, we will describe concrete lessons that were derived from
- those use cases.</p>
+ Afterwards, we will describe lessons derived from the use cases.</p>
<p>We use the term "data cube vocabulary" throughout the document
when referring to the vocabulary.</p>
@@ -339,17 +337,19 @@
<p>The COINS use case leads to the following challenges:</p>
<ul>
- <li>Although not originally not intended, the data cube
- vocabulary could be successfully used for publishing financial data,
- not just statistics.</li>
+ <li>Although not originally intended, the data cube vocabulary
+ could be successfully used for publishing financial data, not just
+ statistics. This has also been shown by the <a
+ href="http://data.gov.uk/resources/payments">Payment Ontology</a>.
+ </li>
<li>Also, the publisher favours a representation that is both as
self-descriptive as possible, i.e., others can link to and download
fully-described individual transactions and as compact as possible,
i.e., information is not unnecessarily repeated. This challenge
supports lesson: <a
- href="#Vocabularyshouldclarifytheuseofsubsetsofobservations">Publishers
- may need more guidance in creating and managing slices or arbitrary
- groups of observations</a>
+ href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">Publishers
+ and consumers may need guidance in checking and making use of
+ well-formedness of published data using data cube</a>
</li>
<li>Moreover, the publisher is thinking about the possible
benefit of publishing slices of the data, e.g., datasets that fix all
@@ -369,39 +369,67 @@
reviewers, links to other useful resources, etc. Being able to trust
that data to be correct and reliable is a central value for
government-published data, so recording provenance is a key
- requirement for the COINS data. This challenge supports lesson: <a
- href="#Vocabularyshouldclarifytheuseofsubsetsofobservations">Publishers
- may need more guidance in creating and managing slices or arbitrary
- groups of observations</a>
+ requirement for the COINS data. For instance, the COINS project [<cite><a
+ href="#ref-COINS">COINS</a></cite>] has at least four perspectives on what
+ they mean by “COINS” data: the abstract notion of “all of COINS”, the
+ data for a particular year, the version of the data for a particular
+ year released on a given date, and the constituent graphs which hold
+ both the authoritative data translated from HMT’s own sources. Also,
+ additional supplementary information which they derive from the data,
+ for example by cross-linking to other datasets. This challenge
+ supports lesson: <a
+ href="#Thereshouldbearecommendedwayofdeclaringrelationsbetweencubes">Publishers
+ may need guidance in making transparent the pre-processing of
+ aggregate statistics</a>
</li>
<li>A challenge also is the size of the data, especially since it
is updated regularly. Five data files already contain between 3.3 and
4.9 million rows of data. This challenge supports lesson: <a
- href="#Vocabularyshouldclarifytheuseofsubsetsofobservations">Publishers
- may need more guidance in creating and managing slices or arbitrary
- groups of observations</a>
+ href="#Thereshouldbemechanismsandrecommendationsregardingpublicationandconsumptionoflargeamountsofstatisticaldata">Publishers
+ and consumers may need more guidance in efficiently processing data
+ using the data cube vocabulary</a>
</li>
</ul>
</section> <section>
<h3 id="PublishingExcelSpreadsheetsasLinkedData">Publisher Use
- Case: Publishing Excel Spreadsheets as Linked Data</h3>
+ Case: Publishing Excel Spreadsheets about Dutch historical census data
+ as Linked Data</h3>
<p>
- <span style="font-size: 10pt">(Part of this use case has been
+ <span style="font-size: 10pt">(This use case has been
contributed by Rinke Hoekstra. See <a
href="http://ehumanities.nl/ceda_r/">CEDA_R</a> and <a
href="http://www.data2semantics.org/">Data2Semantics</a> for more
information.)
</span>
</p>
-
<p>Not only in government, there is a need to publish considerable
amounts of statistical data to be consumed in various (also
unexpected) application scenarios. Typically, Microsoft Excel sheets
- are made available for download. Those excel sheets contain single
- spreadsheets with several multidimensional data tables, having a name
- and notes, as well as column values, row values, and cell values.</p>
- <p>Benefits:</p>
+ are made available for download.</p>
+ <p>
+ For instance, in the <a href="http://ehumanities.nl/ceda_r/">CEDA_R</a>
+ and <a href="http://www.data2semantics.org/">Data2Semantics</a>
+ projects publishing and harmonizing Dutch historical census data (from
+ 1795 onwards) is a goal. These censuses are now only available as
+ Excel spreadsheets (obtained by data entry) that closely mimic the way
+ in which the data was originally published and shall be published as
+ Linked Data.
+ </p>
+
+ <p>Those excel sheets contain single spreadsheets with several
+ multidimensional data tables, having a name and notes, as well as
+ column values, row values, and cell values.</p>
+
+ <p>
+ Another concrete example is the <a
+ href="http://ontowiki.net/Projects/Stats2RDF?show_comments=1">Stats2RDF</a>
+ project that intends to publish biomedical statistical data that is
+ represented as Excel sheets. Here, Excel files are first translated
+ into CSV and then translated into RDF using OntoWiki, a semantic wiki.
+ </p>
+
+ <h4>Benefits</h4>
<ul>
<li>The goal in this use case is to to publish spreadsheet
information in a machine-readable format on the web, e.g., so that
@@ -409,18 +437,6 @@
published data should represent and make available for queries the
most important information in the spreadsheets, e.g., rows, columns,
and cell values.</li>
- <li>For instance, in the <a href="http://ehumanities.nl/ceda_r/">CEDA_R</a>
- and <a href="http://www.data2semantics.org/">Data2Semantics</a>
- projects publishing and harmonizing Dutch historical census data
- (from 1795 onwards) is a goal. These censuses are now only available
- as Excel spreadsheets (obtained by data entry) that closely mimic the
- way in which the data was originally published and shall be published
- as Linked Data.
- </li>
- </ul>
- <p>Challenges in this use case:</p>
-
- <ul>
<li>All context and so all meaning of the measurement point is
expressed by means of dimensions. The pure number is the star of an
ego-network of attributes or dimensions. In a RDF representation it
@@ -429,17 +445,32 @@
different attributes across different value points. This way a
harmonization among variables is performed around the measurement
points themselves.</li>
+ <li>Novel visualisation of census data</li>
+ <li>Possible integration with provenance vocabularies, e.g.,
+ PROV-O, for tracking of harmonization steps</li>
<li>In historical research, until now, harmonization across
datasets is performed by hand, and in subsequent iterations of a
database: it is very hard to trace back the provenance of decisions
- made during the harmonization procedure.</li>
+ made during the harmonization procedure. Publishing the census data
+ as Linked Data may allow (semi-)automatical harmonization.</li>
+ </ul>
+ <h4>Challenges</h4>
+
+ <ul>
+ <li>Semi-structured information, e.g., notes about lineage of
+ data cells, may not be possible to be formalized. This supports
+ lesson <a
+ href="#Thereshouldbearecommendedwayofdeclaringrelationsbetweencubes">Publishers
+ may need guidance in making transparent the pre-processing of
+ aggregate statistics</a>
+ </li>
<li>Combining Data Cube with SKOS [<cite><a
href="#ref-skos">SKOS</a></cite>] to allow for cross-location and
- cross-time historical analysis
+ cross-time historical analysis, supporting lesson <a
+ href="#Vocabularyshouldrecommendamechanismtosupporthierarchicalcodelists">Publishers
+ may need more guidance to decide which representation of hierarchies
+ is most suitable for their use case</a>
</li>
- <li>Novel visualisation of census data</li>
- <li>Integration with provenance vocabularies, e.g., PROV-O, for
- tracking of harmonization steps</li>
<li>These challenges may seem to be particular to the field of
historical research, but in fact apply to government information at
large. Government is not a single body that publishes information at
@@ -450,34 +481,12 @@
<li>Excel sheets provide much flexibility in arranging
information. It may be necessary to limit this flexibility to allow
automatic transformation.</li>
- <li>There are many spreadsheets.</li>
- <li>Semi-structured information, e.g., notes about lineage of
- data cells, may not be possible to be formalized.</li>
+ <li>There may be many spreadsheets which supports lesson <a
+ href="#Thereshouldbemechanismsandrecommendationsregardingpublicationandconsumptionoflargeamountsofstatisticaldata">Publishers
+ and consumers may need more guidance in efficiently processing data
+ using the data cube vocabulary</a></li>
+
</ul>
- <p>Existing work:</p>
- <ul>
- <li>Another concrete example is the <a
- href="http://ontowiki.net/Projects/Stats2RDF?show_comments=1">Stats2RDF</a>
- project that intends to publish biomedical statistical data that is
- represented as Excel sheets. Here, Excel files are first translated
- into CSV and then translated into RDF.
- </li>
- <li>Some of the challenges are met by the work on an ISO
- Extension to SKOS [<cite><a href="#ref-xkos">XKOS</a></cite>].
- </li>
- </ul>
-
-
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#Vocabularyshouldrecommendamechanismtosupporthierarchicalcodelists">Vocabulary
- should recommend a mechanism to support hierarchical code lists</a></li>
- <li><a
- href="#Thereshouldbearecommendedwayofdeclaringrelationsbetweencubes">There
- should be a recommended way of declaring relations between cubes</a></li>
- </ul>
-
</section> <section>
<h3
@@ -542,34 +551,56 @@
<p>This multidimensional data contains for each fact a time
dimension with one level Year and a location dimension with levels
- Unitary Authority, Government Office Region, Country, and ALL.</p>
-
- <p>As unit, units of 1000 households is used.</p>
+ Unitary Authority, Government Office Region, Country, and ALL. As
+ unit, units of 1000 households is used.</p>
<p>In this use case, one wants to publish not only a dataset on the
bottom most level, i.e. what are the number of households at each
Unitary Authority in each year, but also a dataset on more aggregated
- levels.</p>
-
- <p>For instance, in order to publish a dataset with the number of
+ levels. For instance, in order to publish a dataset with the number of
households at each Government Office Region per year, one needs to
aggregate the measure of each fact having the same Government Office
Region using the SUM function.</p>
- <p>Importantly, one would like to maintain the relationship between
- the resulting datasets, i.e., the levels and aggregation functions.</p>
+ <p>Similarly, for many uses then population broken down by some
+ category (e.g. ethnicity) is expressed as a percentage. Separate
+ datasets give the actual counts per category and aggregate counts. In
+ such cases it is common to talk about the denominator (often DENOM)
+ which is the aggregate count against which the percentages can be
+ interpreted.</p>
- <p>Again, this use case does not simply need a selection (or "dice"
- in OLAP context) where one fixes the time period dimension.</p>
-
- <p>Requirements:</p>
+ <h4>Benefits</h4>
<ul>
- <li><a
- href="#Vocabularyshouldrecommendamechanismtosupporthierarchicalcodelists">Vocabulary
- should recommend a mechanism to support hierarchical code lists</a></li>
+ <li>Expressing aggregation relationships would allow engines to
+ automatically derive statistics on higher aggregation levels.</li>
+ <li>Vice versa, representing further aggregated datasets would
+ allow to answer queries with a simple lookup instead of computations
+ which may be more time consuming or require specific features of the
+ query engine.</li>
</ul>
+ <h4>Challenges</h4>
+ <ul>
+ <li>Importantly, one would like to maintain the relationship
+ between the resulting datasets, i.e., the levels and aggregation
+ functions. Again, this use case does not simply need a selection (or
+ "dice" in OLAP context) where one fixes the time period dimension.
+ This supports lesson <a
+ href="#Thereshouldbearecommendedmechanismtoallowforpublicationofaggregateswhichcrossmultipledimensions">Publishers
+ may need guidance in how to represent common analytical operations
+ such as Slice, Dice, Rollup on data cubes</a>
+ </li>
+ <li>Literals that are used in observations, cannot be used as
+ subjects in triples. So, no hierarchies can be defined that would for
+ example link integer years via skos:narrower to months. This supports
+ lesson <a
+ href="#Vocabularyshouldrecommendamechanismtosupporthierarchicalcodelists">Publishers
+ may need more guidance to decide which representation of hierarchies
+ is most suitable for their use case</a>.
+ </li>
+ </ul>
+
</section> <section>
<h3 id="PublishingslicesofdataaboutUKBathingWaterQuality">Publisher
Use Case: Publishing Observational Data Sets about UK Bathing Water
@@ -605,11 +636,31 @@
</ul>
<p>The most important dimensions of the data are bathing water,
sampling point, and compliance classification.</p>
- <p>Challenges:</p>
+
+ <h4>Benefits</h4>
+ <ul>
+ <li>The bathing-water dataset (documentation) is structured
+ around the use of the data cube vocabulary and fronted by a linked
+ data API configuration which makes the data available for re-use in
+ additional formats such as JSON and CSV.</li>
+ <li>Publishing bathing-water quality information in this way will
+ enable the Environment Agency to meet the needs of its many data
+ consumers in a uniform way rather than through diverse pairwise
+ arrangements; preempt requests for specific data; and enable a larger
+ community of web and mobile application developers and value-added
+ information aggregators to use and re-use bathing-water quality
+ information sourced by the environment agency.</li>
+ </ul>
+
+ <h4>Challenges</h4>
<ul>
<li>Observations may exhibit a number of attributes, e.g.,
- whether ther was an abnormal weather exception.</li>
- <li>Relevant slices of both datasets are to be created:
+ whether there was an abnormal weather exception.</li>
+ <li>Relevant slices of both datasets are to be created, which
+ supports lesson <a
+ href="#Vocabularyshouldclarifytheuseofsubsetsofobservations">Publishers
+ may need more guidance in creating and managing slices or arbitrary
+ groups of observations</a>:
<ul>
<li>Annual Compliance Assessment Dataset: all the observations
for a specific sampling point, all the observations for a specific
@@ -622,35 +673,113 @@
observations, e.g., collecting all the "latest" observations in a
continuously updated data set.</li>
</ul>
-
-
+ </li>
+ <li>In this use case, observation and measurement data is to be
+ published which per se is not aggregated statistics. The <a
+ href="http://purl.oclc.org/NET/ssnx/ssn">Semantic Sensor Network
+ ontology</a> (SSN) already provides a way to publish sensor information.
+ SSN data provides statistical Linked Data and grounds its data to the
+ domain, e.g., sensors that collect observations (e.g., sensors
+ measuring average of temperature over location and time). Still, this
+ case study has shown that the data cube vocabulary may be a useful
+ alternative and can be successfully used for observation and
+ measurement data, as well as statistical data.
</li>
</ul>
- <p>Existing Work:</p>
+ </section> <section>
+ <h3 id="MetOfficeCaseStudy">Publisher Case study: Site specific
+ weather forecasts from Met Office, the UK's National Weather Service</h3>
+ <span style="font-size: 10pt">(This section contributed by Dave
+ Reynolds)</span>
+
+ <p>The Met Office, the UK's National Weather Service, provides a
+ range of weather forecast products including openly available
+ site-specific forecasts for the UK. The site specific forecasts cover
+ over 5000 forecast points, each forecast predicts 10 parameters and
+ spans a 5 day window at 3 hourly intervals, the whole forecast is
+ updated each hour. A proof of concept project investigated the
+ challenge of publishing this information as linked data using the Data
+ Cube vocabulary.</p>
+
+ <h4>Benefits</h4>
<ul>
- <li>The <a href="http://purl.oclc.org/NET/ssnx/ssn">Semantic
- Sensor Network ontology</a> (SSN) already provides a way to publish
- sensor information. SSN data provides statistical Linked Data and
- grounds its data to the domain, e.g., sensors that collect
- observations (e.g., sensors measuring average of temperature over
- location and time).
- </li>
- <li>A number of organizations, particularly in the Climate and
- Meteorological area already have some commitment to the OGC
- "Observations and Measurements" (O&M) logical data model, also
- published as ISO 19156.</li>
+ <li>Explicit metadata describing the forecast process, coverage
+ and phenomena being forecast; making the data self-describing.</li>
+
+ <li>Linking to other linked data resources (particularly
+ geographic regions and named places associated with the forecast
+ locations) enabling discovery of related data.</li>
+
+ <li>Ability to define slices through the data for convenient
+ consumption by applications.</li>
</ul>
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#VocabularyshoulddefinerelationshiptoISO19156ObservationsMeasurements">Vocabulary
- should define relationship to ISO19156 - Observations & Measurements</a></li>
- <li><a
- href="#Vocabularyshouldclarifytheuseofsubsetsofobservations">Vocabulary
- should clarify the use of subsets of observations</a></li>
- </ul>
+ <h4>Challenges</h4>
+ <h5>ISO19156 compatibility</h5>
+ <p>
+ The World Meteorological Organization (WMO) develops and recommends
+ data interchange standard and within that community compatibility with
+ ISO19156 <em>"Geographic information — Observations and
+ measurements"</em> (O&M) is regarded as important. Thus, this supports
+ lesson <a
+ href="#VocabularyshoulddefinerelationshiptoISO19156ObservationsMeasurements">Modelers
+ using ISO19156 - Observations & Measurements may need clarification
+ regarding the relationship to the data cube vocabulary</a>
+ </p>
+ <b>Solution:</b>
+ <p>O&M provides a data model for an Observation with associated
+ Phenomenon, measurement ProcessUsed, Domain (feature of interest) and
+ Result. Prototype vocabularies developed at CSIRO and extended within
+ this project allow this data model to be represented in RDF. For the
+ site specific forecasts then a 5-day forecast for all 5000+ sites is
+ regarded as a single O&M Observation.</p>
+ <p>
+ To represent the forecast data itself, the Result in the O&M model,
+ then the relevant standard is ISO19123 <em>"Geographic
+ information — Schema for coverage geometry and functions"</em>. This
+ provides a data model for a Coverage which can represent a set of
+ values across some space. It defines different types of Coverage
+ including a DiscretePointCoverage suited to representing site-specific
+ forecast results.
+ </p>
+ <p>It turns out that it is straightforward to treat an RDF Data
+ Cube as a particular concrete representation of the
+ DiscretePointCoverage logical model. The cube has dimensions
+ corresponding to the forecast time and location and the measure is a
+ record representing the forecast values of the 10 phenomena. Slices by
+ time and location provide subsets of the data that directly match the
+ data packages supported by an existing on-line service.</p>
+ <p>
+ Note that in this situation an <em>observation</em> in the sense of
+ <code>qb:Observation</code>
+ and an <em>observation</em> in the sense of ISO19156 Observations and
+ Measurements are different things. The O&M Observation is the whole
+ forecast whereas each
+ <code>qb:Observation</code>
+ corresponds to a single GeometryValuePair within the forecast results
+ Coverage.
+ </p>
+
+ </p>
+ <h5>Data volume</h5>
+ <p>
+ Each hourly update comprises over 2 million data points and forecast
+ data is requested by a large number of data consumers. Bandwidth costs
+ are thus a key consideration and the apparent verbosity of RDF in
+ general, and Data Cube specifically, was a concern. This supports
+ lesson <a
+ href="#Thereshouldbemechanismsandrecommendationsregardingpublicationandconsumptionoflargeamountsofstatisticaldata">
+ Publishers and consumers may need more guidance in efficiently
+ processing data using the data cube vocabulary.</a>
+ </p>
+ <b>Solution:</b>
+ <p>Regarding bandwidth costs then the key is not raw data volume
+ but compressibility, since such data is transmitted in compressed
+ form. A Turtle representation of an non-abbreviated data cube
+ compressed to within 15-20% of the size of compressed, handcrafted XML
+ and JSON representations. Thus obviating the need for abbreviations or
+ custom serialization.</p>
</section> <section>
<h3 id="EurostatSDMXasLinkedData">Publisher Use Case: Eurostat
@@ -707,7 +836,7 @@
</p>
- <p>Benefits:</p>
+ <h4>Benefits</h4>
<ul>
<li>Possible implementation of ETL pipelines based on Linked Data
@@ -724,24 +853,26 @@
<li>Allows to reuse single observations from the data.</li>
<li>Linking to information from other data sources, e.g., for
- geo-spatial dimension.
+ geo-spatial dimension.</li>
</ul>
- <p>Challenges:</p>
+ <h4>Challenges</h4>
<ul>
<li>New Eurostat datasets are added regularly to Eurostat. The
Linked Data representation should automatically provide access to the
most-up-to-date data.</li>
- <li>How to match elements of the geo-spatial dimension to
- elements of other data sources, e.g., NUTS, GADM.</li>
-
<li>There is a large number of Eurostat datasets, each possibly
containing a large number of columns (dimensions) and rows
(observations). Eurostat publishes more than 5200 datasets, which,
when converted into RDF require more than 350GB of disk space
- yielding a dataspace with some 8 billion triples.</li>
+ yielding a dataspace with some 8 billion triples. This supports
+ lesson <a
+ href="#Thereshouldbemechanismsandrecommendationsregardingpublicationandconsumptionoflargeamountsofstatisticaldata">
+ Publishers and consumers may need more guidance in efficiently
+ processing data using the data cube vocabulary.</a>
+ </li>
<li>In the Eurostat Linked Data Wrapper, there is a timeout for
transforming SDMX to Linked Data, since Google App Engine is used.
@@ -749,18 +880,27 @@
would be needed.</li>
<li>Provide a useful interface for browsing and visualising the
- data. One problem is that the data sets have to high dimensionality
+ data. One problem is that the data sets have too high dimensionality
to be displayed directly. Instead, one could visualise slices of time
series data. However, for that, one would need to either fix most
other dimensions (e.g., sex) or aggregate over them (e.g., via
average). The selection of useful slices from the large number of
- possible slices is a challenge.</li>
+ possible slices is a challenge. This supports lesson <a
+ href="#Vocabularyshouldclarifytheuseofsubsetsofobservations">
+ Publishers may need more guidance in creating and managing slices or
+ arbitrary groups of observations</a>.
+ </li>
<li>Each dimension used by a dataset has a range of permitted
values that need to be described.</li>
<li>The Eurostat SDMX as Linked Data use case suggests to have
- time lines on data aggregating over the gender dimension.</li>
+ time lines on data aggregating over the gender dimension. This
+ supports lesson <a
+ href="#Thereshouldbearecommendedmechanismtoallowforpublicationofaggregateswhichcrossmultipledimensions">
+ Publishers may need guidance in how to represent common analytical
+ operations such as Slice, Dice, Rollup on data cubes</a>.
+ </li>
<li>The Eurostat SDMX as Linked Data use case suggests to provide
data on a gender level and on a level aggregating over the gender
@@ -770,8 +910,8 @@
<ul>
<li>Eurostat - Linked Data pulls in changes from the original
- Eurostat dataset on weekly basis and conversion process runs every
- Saturday at noon taking into account new datasets along with
+ Eurostat dataset on a weekly basis and the conversion process runs
+ every Saturday at noon taking into account new datasets along with
updates to existing datasets.</li>
<li>Eurostat Linked Data Wrapper on-the-fly translates Eurostat
datasets into RDF so that always the most current data is used. The
@@ -794,47 +934,48 @@
<ul>
<li>Eurostat - Linked Data provides SPARQL endpoint for the
metadata (not the observations).</li>
- <li>Eurostat Linked Data Wrapper allows and demonstrates how to
- use Qcrumb.com to query the data.</li>
+ <li>Eurostat Linked Data Wrapper provides resolvable URIs to
+ datasets that return all observations of the dataset. Also, every
+ dataset serves the URI of its data structure definition (dsd). The
+ dsd URI returns all RDF describing the dataset. Separating
+ information resources for dataset and data structure definition
+ allows for example to first gather the dsd and only for actual query
+ execution resolve ds URIs.</li>
</ul>
<li>Browsing and visualising interface:
<ul>
<li>Eurostat Linked Data Wrapper provides for each dataset an
- HTML page showing a visualisation of the data.</li>
+ HTML page showing a JavaScript-based visualisation of the data.
+ This also supports lesson <a
+ href="#Consumersmayneedguidanceinconversionsintoformats">
+ Consumers may need guidance in conversions into formats that can
+ easily be displayed and further investigated in tools such as
+ Google Data Explorer, R, Weka etc.</a>.
+ </li>
</ul>
</li>
- </ul>
-
- <p>Non-requirements:</p>
- <ul>
<li>One possible application would run validation checks over
- Eurostat data. The intended standard vocabulary is to publish the
- Eurostat data as-is and is not intended to represent information for
- validation (similar to business rules).</li>
- <li>Information of how to match elements of the geo-spatial
- dimension to elements of other data sources, e.g., NUTS, GADM, is not
- part of a vocabulary recommendation.</li>
+ Eurostat data. However, the data cube vocabulary is to publish
+ statistical data as-is and is not intended to represent information
+ for validation (similar to business rules).</li>
+ <li>An application could try to automatically match elements of
+ the geo-spatial dimension to elements of other data sources, e.g.,
+ NUTS, GADM. In Eurostat Linked Data wrapper this is done by simple
+ URI guessing from external data sources. Automatic linking datasets
+ or linking datasets with metadata is not part of data cube
+ vocabulary.</li>
</ul>
- <p>Requirements:</p>
- <ul>
- <li><a href="#VocabularyshouldbuildupontheSDMXinformationmodel">There
- should be mechanisms and recommendations regarding publication and
- consumption of large amounts of statistical data</a></li>
- <li><a
- href="#Thereshouldbearecommendedmechanismtoallowforpublicationofaggregateswhichcrossmultipledimensions">There
- should be a recommended mechanism to allow for publication of
- aggregates which cross multiple dimensions</a></li>
- </ul>
</section> <section>
<h3 id="Representingrelationshipsbetweenstatisticaldata">Publisher
- Use Case: Representing relationships between statistical data</h3>
+ Case Study: Improving trust in published sustainability information at
+ the Digital Enterprise Research Institute (DERI)</h3>
<p>
<span style="font-size: 10pt">(This use case has mainly been
- taken from the COINS project [<cite><a href="#ref-COINS">COINS</a></cite>])
+ taken from [<cite><a href="#ref-COGS">COGS</a></cite>])
</span>
</p>
@@ -848,47 +989,20 @@
published.</p>
<p>
- For instance, the COINS project [<cite><a href="#ref-COINS">COINS</a></cite>]
- has at least four perspectives on what they mean by “COINS” data: the
- abstract notion of “all of COINS”, the data for a particular year, the
- version of the data for a particular year released on a given date,
- and the constituent graphs which hold both the authoritative data
- translated from HMT’s own sources. Also, additional supplementary
- information which they derive from the data, for example by
- cross-linking to other datasets.
+ A concrete example is given by Freitas et al. [<cite><a
+ href="#ref-COGS">COGS</a></cite>], where transformations on financial
+ datasets, e.g., addition of derived measures, conversion of units,
+ aggregations, OLAP operations, and enrichment of statistical data are
+ executed on statistical data before showing them in a web-based
+ report.
</p>
- <p>Another specific use case is that the Welsh Assembly government
- publishes a variety of population datasets broken down in different
- ways. For many uses then population broken down by some category (e.g.
- ethnicity) is expressed as a percentage. Separate datasets give the
- actual counts per category and aggregate counts. In such cases it is
- common to talk about the denominator (often DENOM) which is the
- aggregate count against which the percentages can be interpreted.</p>
-
<p>
- Another example for representing relationships between statistical
- data are transformations on datasets, e.g., addition of derived
- measures, conversion of units, aggregations, OLAP operations, and
- enrichment of statistical data. A concrete example is given by Freitas
- et al. [<cite><a href="#ref-COGS">COGS</a></cite>] and illustrated in
- the following figure.
+ See <a href="http://treo.deri.ie/cogs/example/swpm2012.htm">SWPM
+ 2012 Provenance Example</a> for screenshots.
</p>
- <p class="caption">Figure: Illustration of ETL workflows to process
- statistics</p>
-
- <p align="center">
- <img alt="COGS relationships between statistics example"
- src="./figures/Relationships_Statistical_Data_Cogs_Example.png"></img>
- </p>
-
- <p>Here, numbers from a sustainability report have been created by
- a number of transformations to statistical data. Different numbers
- (e.g., 600 for year 2009 and 503 for year 2010) might have been
- created differently, leading to different reliabilities to compare
- both numbers.</p>
- <p>Benefits:</p>
+ <h4>Benefits</h4>
<p>Making transparent the transformation a dataset has been exposed
to. Increases trust in the data.</p>
@@ -911,28 +1025,22 @@
</li>
<li>If so should that be scoped to simple, common relationships
like DENOM or allow expression of arbitrary mathematical relations?</li>
- </ul>
- <p>
- Existing Work:
- <ul>
- <li>Possible relation to <a
- href="http://www.w3.org/2011/gld/wiki/Best_Practices_Discussion_Summary#Versioning">Versioning</a>
- part of GLD Best Practices Document, where it is specified how to
- publish data which has multiple versions.
- </li>
- <li>The <a href="http://sites.google.com/site/cogsvocab/">COGS</a>
- vocabulary [<cite><a href="#ref-COGS">COGS</a></cite>] is related to
- this use case since it may complement the standard vocabulary for
- representing ETL pipelines processing statistics.
- </li>
- </ul>
- </p>
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#Thereshouldbearecommendedwayofdeclaringrelationsbetweencubes">There
- should be a recommended way of declaring relations between cubes</a></li>
+ <li>This use case opens up questions regarding versioning of
+ statistical Linked Data. Thus, there is a possible relation to <a
+ href="http://www.w3.org/2011/gld/wiki/Best_Practices_Discussion_Summary#Versioning">Versioning</a>
+ part of GLD Best Practices Document, where it is specified how to
+ publish data which has multiple versions.
+ </li>
+ <li>In this use case, the <a
+ href="http://sites.google.com/site/cogsvocab/">COGS</a> vocabulary [<cite><a
+ href="#ref-COGS">COGS</a></cite>] has shown to complement the data cube
+ vocabulary w.r.t. representing ETL pipelines processing statistics.
+ This supports lesson <a
+ href="#Thereshouldbearecommendedwayofdeclaringrelationsbetweencubes">
+ Publishers may need guidance in making transparent the
+ pre-processing of aggregate statistics</a>.
+ </li>
</ul>
</section> <section>
@@ -963,7 +1071,7 @@
queried and visualized in simple charts, e.g., line diagrams.
</p>
- <p class="caption">Figure: HTML embedded line chart of an
+ <p class="caption">Figure 1: HTML embedded line chart of an
environmental measure over time for three regions in the lower Jordan
valley</p>
@@ -973,31 +1081,33 @@
src="./figures/Level_above_msl_3_locations.png" width="1000px"></img>
</p>
- <p class="caption">Figure: Showing the same data in a pivot table.
- Here, the aggregate COUNT of measures per cell is given.</p>
+ <p class="caption">Figure 2: Showing the same data in a pivot table
+ aggregating to single months. Here, the aggregate COUNT of measures
+ per cell is given.</p>
<p align="center">
<img
alt="Figure: Showing the same data in a pivot
- table. Here, the aggregate COUNT of measures per cell is given."
+ table aggregating to single months. Here, the aggregate COUNT of measures per cell is given."
src="./figures/pivot_analysis_measurements.PNG"></img>
</p>
- <p>Challenges of this use case are:</p>
+ <h4>Benefits</h4>
+ <p>Easy, flexible and powerful visualisations of published
+ statistical data.</p>
+
+ <h4>Challenges</h4>
<ul>
<li>The difficulties lay in structuring the data appropriately so
- that the specific information can be queried.</li>
+ that the specific information can be queried. This supports lesson <a
+ href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">
+ Publishers and consumers may need guidance in checking and making
+ use of well-formedness of published data using data cube</a>.
+ </li>
<li>Also, data shall be published with having potential
integration in mind. Therefore, e.g., units of measurements need to
be represented.</li>
<li>Integration becomes much more difficult if publishers use
different measures, dimensions.</li>
</ul>
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">There
- should be criteria for well-formedness and assumptions consumers can
- make about published data</a></li>
- </ul>
</section> <section>
<h3 id="VisualisingpublishedstatisticaldatainGooglePublicDataExplorer">Consumer
@@ -1027,7 +1137,7 @@
<p>For instance, Eurostat data about Unemployment rate downloaded
from the web as shown in the following figure:</p>
- <p class="caption">Figure: An interactive chart in GPDE for
+ <p class="caption">Figure 3: An interactive chart in GPDE for
visualising Eurostat data described with DSPL</p>
<p align="center">
<img
@@ -1035,44 +1145,42 @@
src="./figures/Eurostat_GPDE_Example.png" width="1000px"></img>
</p>
- <p>Benefits:</p>
+ <p>There are different possible approaches each having advantages
+ and disadvantages: 1) A customer C is downloading this data into a
+ triple store; SPARQL queries on this data can be used to transform the
+ data into DSPL and uploaded and visualized using GPDE. 2) or, one or
+ more XLST transformation on the RDF/XML transforms the data into DSPL.</p>
+
+ <h4>Benefits</h4>
<ul>
- <li>If a standard Linked Data vocabulary is used, visualising and
- exploring new data that already is represented using this vocabulary
- can easily be done using GPDE.</li>
- <li>Datasets can be first integrated using Linked Data technology
- and then analysed using GDPE.</li>
+ <li>Easy to visualise QB data.</li>
+ <li>There could be a process of first transforming data into RDF
+ for further preprocessing and integration and then of loading it into
+ GPDE for visualisation.</li>
+ <li>Linked Data could provide the way to automatically load data
+ from a data source whereas GPDE is only for visualisation.</li>
</ul>
- <p>Challenges of this use case are:</p>
+ <h4>Challenges</h4>
<ul>
- <li>There are different possible approaches each having
- advantages and disadvantages: 1) A customer C is downloading this
- data into a triple store; SPARQL queries on this data can be used to
- transform the data into DSPL and uploaded and visualized using GPDE.
- 2) or, one or more XLST transformation on the RDF/XML transforms the
- data into DSPL.</li>
<li>The technical challenges for the consumer here lay in knowing
where to download what data and how to get it transformed into DSPL
- without knowing the data.</li>
+ without knowing the data. This supports lesson <a
+ href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">
+ Publishers and consumers may need guidance in checking and making
+ use of well-formedness of published data using data cube</a>.
+ </li>
+ <li>Define a mapping between data cube and DSPL. DSPL is
+ representative for using statistical data published on the web in
+ available tools for analysis. Similar tools that may be automatically
+ covered are: Weka (arff data format), Tableau, SPSS, STATA, PC-Axis
+ etc. This supports lesson <a
+ href="#Consumersmayneedguidanceinconversionsintoformats">
+ Consumers may need guidance in conversions into formats that can
+ easily be displayed and further investigated in tools such as Google
+ Data Explorer, R, Weka etc.</a>.
+ </li>
</ul>
- <p>
- Non-requirements:
- <ul>
- <li>DSPL is representative for using statistical data published
- on the web in available tools for analysis. Similar tools that may
- be automatically covered are: Weka (arff data format), Tableau,
- SPSS, STATA, PC-Axis etc.</li>
- </ul>
- </p>
-
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">There
- should be criteria for well-formedness and assumptions consumers can
- make about published data</a></li>
- </ul>
</section> <section>
<h3 id="AnalysingpublishedstatisticaldatawithcommonOLAPsystems">Consumer
Use Case: Analysing published statistical data with common OLAP
@@ -1113,9 +1221,9 @@
<p>
An example scenario of this use case is the Financial Information
Observation System (FIOS) [<cite><a href="#ref-FIOS">FIOS</a></cite>],
- where XBRL data provided by the SEC on the web is to be re-published
- as Linked Data and made possible to explore and analyse by
- stakeholders in a web-based OLAP client Saiku.
+ where XBRL data provided by the SEC on the web is re-published as
+ Linked Data and made possible to explore and analyse by stakeholders
+ in a web-based OLAP client Saiku.
</p>
<p>The following figure shows an example of using FIOS. Here, for
@@ -1125,14 +1233,14 @@
given:</p>
- <p class="caption">Figure: Example of using FIOS for OLAP
+ <p class="caption">Figure 4: Example of using FIOS for OLAP
operations on financial data</p>
<p align="center">
<img alt="Example of using FIOS for OLAP operations on financial data"
src="./figures/FIOS_example.PNG"></img>
</p>
- <p>Benefits:</p>
+ <h4>Benefits</h4>
<ul>
<li>OLAP operations cover typical business requirements, e.g.,
@@ -1142,37 +1250,45 @@
<li>OLAP functionality provided by many tools that may be reused</li>
</ul>
- <p>Challenges:</p>
+ <h4>Challenges</h4>
<ul>
<li>ETL pipeline needs to automatically populate a data
warehouse. Common OLAP systems use relational databases with a star
- schema.</li>
+ schema. This supports lesson <a
+ href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">
+ Publishers and consumers may need guidance in checking and making
+ use of well-formedness of published data using data cube</a>.
+ </li>
<li>A problem lies in the strict separation between queries for
the structure of data (metadata queries), and queries for actual
aggregated values (OLAP operations).</li>
+ <li>Define a mapping between OLAP operations and operations on
+ data using the data cube vocabulary. This supports lesson <a
+ href="#Thereshouldbearecommendedmechanismtoallowforpublicationofaggregateswhichcrossmultipledimensions">
+ Publishers may need guidance in how to represent common analytical
+ operations such as Slice, Dice, Rollup on data cubes</a>.
+ </li>
<li>Another problem lies in defining Data Cubes without greater
- insight in the data beforehand.</li>
+ insight in the data beforehand. Thus, OLAP systems have to cater for
+ possibly missing information (e.g., the aggregation function or a
+ human readable label).</li>
<li>Depending on the expressivity of the OLAP queries (e.g.,
aggregation functions, hierarchies, ordering), performance plays an
- important role.</li>
- <li>Olap systems have to cater for possibly missing information
- (e.g., the aggregation function or a human readable label).</li>
+ important role. This supports lesson <a
+ href="#Thereshouldbemechanismsandrecommendationsregardingpublicationandconsumptionoflargeamountsofstatisticaldata">
+ Publishers and consumers may need more guidance in efficiently
+ processing data using the data cube vocabulary</a>.
+ </li>
</ul>
-
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">There
- should be criteria for well-formedness and assumptions consumers can
- make about published data</a></li>
- </ul>
</section> <section>
<h3 id="Registeringpublishedstatisticaldataindatacatalogs">Registry
Use Case: Registering published statistical data in data catalogs</h3>
<p>
<span style="font-size: 10pt">(Use case motivated by <a
- href="http://www.w3.org/TR/vocab-dcat/">Data Catalog vocabulary</a>)
+ href="http://www.w3.org/TR/vocab-dcat/">Data Catalog vocabulary</a>
+ and <a href="http://wiki.planet-data.eu/web/Datasets">RDF Data
+ Cube Vocabulary datasets</a> in the PlanetData Wiki)
</span>
</p>
@@ -1201,34 +1317,29 @@
and selection - and to provide a useful overview of RDF Data Cube
deployments in the Linked Data cloud.
</p>
+ <h4>Benefits</h4>
+ <p>Potential consumers will be pointed to published statistics.</p>
- <p>Unanticipated Uses:</p>
-
+ <h4>Challenges</h4>
<ul>
- <li>If data catalogs contain statistics, they do not expose those
- using Linked Data but for instance using CSV or HTML (e.g., Pangea).
- It could also be a use case to publish such data using the data cube
- vocabulary.</li>
+ <li>Define mapping between DCAT and data cube vocabulary. The <a
+ href="http://www.w3.org/TR/vocab-dcat/">Data Catalog vocabulary</a>
+ (DCAT) is strongly related to this use case since it may complement
+ the standard vocabulary for representing statistics in the case of
+ registering data in a data catalog. This supports lesson <a
+ href="#Thereshouldbemechanismsandrecommendationsregardingpublicationandconsumptionoflargeamountsofstatisticaldata">Publishers
+ may need guidance in communicating the availability of published
+ statistical data to external parties and to allow automatic
+ discovery of statistical data</a>
+ </li>
+ <li>Define mapping between data cube vocabulary and data
+ catalogue descriptions. If data catalogs contain statistics, they do
+ not expose those using Linked Data but for instance using CSV or HTML
+ (e.g., Pangea). Therefore, it could also be a use case to publish
+ such data using the data cube vocabulary. An example would be data
+ described using the Data Documentation Initiative (DDI).</li>
</ul>
- <p>Existing Work:</p>
- <ul>
- <li>The <a href="http://www.w3.org/TR/vocab-dcat/">Data
- Catalog vocabulary</a> (DCAT) is strongly related to this use case since
- it may complement the standard vocabulary for representing statistics
- in the case of registering data in a data catalog.
- </li>
- </ul>
-
-
- <p>Requirements:</p>
- <ul>
- <li><a
- href="#Thereshouldbearecommendedwaytocommunicatetheavailabilityofpublishedstatisticaldatatoexternalpartiesandtoallowautomaticdiscoveryofstatisticaldata">There
- should be a recommended way to communicate the availability of
- published statistical data to external parties and to allow
- automatic discovery of statistical data</a></li>
- </ul>
</section> </section>
<section>
@@ -1256,18 +1367,6 @@
<li>Issue: <a href="http://www.w3.org/2011/gld/track/issues/37">http://www.w3.org/2011/gld/track/issues/37</a></li>
</ul>
- <p>Required by:</p>
- <ul>
- <li><a href="#SDMXWebDisseminationUseCase">SDMX Web
- Dissemination Use Case</a></li>
- <li><a
- href="#UKgovernmentfinancialdatafromCombinedOnlineInformationSystem">Publisher
- Use Case: UK government financial data from Combined Online
- Information System (COINS)</a></li>
- <li><a href="#EurostatSDMXasLinkedData">Publisher Use Case:
- Eurostat SDMX as Linked Data</a></li>
- </ul>
-
</section> <section>
<h3 id="Vocabularyshouldclarifytheuseofsubsetsofobservations">Publishers
may need more guidance in creating and managing slices or arbitrary
@@ -1287,16 +1386,6 @@
</li>
</ul>
- <p>Required by:</p>
- <ul>
- <li><a
- href="#UKgovernmentfinancialdatafromCombinedOnlineInformationSystem">Publisher
- Use Case: UK government financial data from Combined Online
- Information System (COINS)</a></li>
- <li><a href="#PublishingslicesofdataaboutUKBathingWaterQuality">Publisher
- Use Case: Publishing slices of data about UK Bathing Water Quality</a></li>
- </ul>
-
</section> <section>
<h3
id="Vocabularyshouldrecommendamechanismtosupporthierarchicalcodelists">Publishers
@@ -1336,12 +1425,7 @@
<li>Part of the requirement is met by the work on an ISO
Extension to SKOS [<cite><a href="#ref-xkos">XKOS</a></cite>]
</li>
- </ul>
-
- <p>Required by:</p>
- <ul>
- <li><a href="#PublishingExcelSpreadsheetsasLinkedData">Publisher
- Use Case: Publishing Excel Spreadsheets as Linked Data</a></li>
+ <li>Issue: <a href="http://www.w3.org/2011/gld/track/issues/59">http://www.w3.org/2011/gld/track/issues/59</a></li>
</ul>
</section> <section>
@@ -1360,11 +1444,12 @@
<li>Issue: <a href="http://www.w3.org/2011/gld/track/issues/32">http://www.w3.org/2011/gld/track/issues/32</a></li>
</ul>
- <p>Required by:</p>
- <ul>
- <li><a href="#PublishingslicesofdataaboutUKBathingWaterQuality">Publisher
- Use Case: Publishing slices of data about UK Bathing Water Quality</a></li>
- </ul>
+ <p>
+ Partly solved by description for <a
+ href="#publisher-case-study-site-specific-weather-forecasts-from-met-office-the-uk-s-national-weather-service">Publisher
+ Case study: Site specific weather forecasts from Met Office, the UK's
+ National Weather Service</a>.
+ </p>
</section> <section>
<h3
@@ -1377,18 +1462,6 @@
<li>Issue: <a href="http://www.w3.org/2011/gld/track/issues/31">http://www.w3.org/2011/gld/track/issues/31</a></li>
</ul>
- <p>Required by:</p>
- <ul>
- <li>E.g., the Eurostat SDMX as Linked Data use case suggests to
- have time lines on data aggregating over the gender dimension: <a
- href="#EurostatSDMXasLinkedData">Publisher Use Case: Eurostat
- SDMX as Linked Data</a>
- </li>
- <li>Another possible use case could be provided by the <a
- href="http://data.gov.uk/resources/payments">Payment Ontology</a>.
- </li>
- </ul>
-
</section> <section>
<h3 id="Thereshouldbearecommendedwayofdeclaringrelationsbetweencubes">Publishers
may need guidance in making transparent the pre-processing of
@@ -1402,12 +1475,6 @@
</li>
</ul>
- <p>Required by:</p>
- <ul>
- <li><a href="#Representingrelationshipsbetweenstatisticaldata">Publisher
- Use Case: Representing relationships between statistical data</a></li>
- </ul>
-
</section> <section>
<h3
id="Thereshouldbecriteriaforwell-formednessandassumptionsconsumerscanmakeaboutpublisheddata">Publishers
@@ -1419,20 +1486,26 @@
<li>Issue: <a href="http://www.w3.org/2011/gld/track/issues/29">http://www.w3.org/2011/gld/track/issues/29</a></li>
</ul>
- <p>Required by:</p>
+ </section> <section>
+ <h3
+ id="Publishersmayneedguidanceinconversionsfromcommonstatisticalrepresentations">Publishers
+ may need guidance in conversions from common statistical
+ representations such as CSV, Excel, ARFF etc.</h3>
+
+ <p>Background information:</p>
<ul>
- <li><a
- href="#Simplechartvisualisationsofpublishedstatisticaldata">Consumer
- Use Case: Simple chart visualisations of (integrated) published
- statistical data</a></li>
- <li><a
- href="#VisualisingpublishedstatisticaldatainGooglePublicDataExplorer">Consumer
- Use Case: Visualising published statistical data in Google Public
- Data Explorer</a></li>
- <li><a
- href="#AnalysingpublishedstatisticaldatawithcommonOLAPsystems">Consumer
- Use Case: Analysing published statistical data with common OLAP
- systems</a></li>
+ <li>None.</li>
+ </ul>
+
+ </section> <section>
+ <h3 id="Consumersmayneedguidanceinconversionsintoformats">Consumers
+ may need guidance in conversions into formats that can easily be
+ displayed and further investigated in tools such as Google Data
+ Explorer, R, Weka etc.</h3>
+
+ <p>Background information:</p>
+ <ul>
+ <li>None.</li>
</ul>
</section> <section>
@@ -1447,12 +1520,6 @@
</li>
</ul>
- <p>Required by:</p>
- <ul>
- <li><a href="#EurostatSDMXasLinkedData">Publisher Use Case:
- Eurostat SDMX as Linked Data</a></li>
- </ul>
-
</section> <section>
<h3
id="Thereshouldbearecommendedwaytocommunicatetheavailabilityofpublishedstatisticaldatatoexternalpartiesandtoallowautomaticdiscoveryofstatisticaldata">Publishers
@@ -1465,14 +1532,6 @@
<li>None.</li>
</ul>
- <p>Required by:</p>
- <ul>
- <li><a href="#SDMXWebDisseminationUseCase">SDMX Web
- Dissemination Use Case</a></li>
- <li><a href="#Registeringpublishedstatisticaldataindatacatalogs">Registry
- Use Case: Registering published statistical data in data catalogs</a></li>
- </ul>
-
</section> </section>
<section class="appendix">
<h2 id="acknowledgements">Acknowledgements</h2>