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+++ b/data-cube/index.html Fri Feb 10 19:14:41 2012 +0000
@@ -8,29 +8,12 @@
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@@ -52,58 +35,12 @@
statistical data flows.</p>
</section>
-<hr>
+<section id="introduction">
+<h2>Introduction</h2>
-<h2 id="toc">Table of Contents</h2>
-<ul class="toc">
- <li><a href="#introduction">1. Introduction</a>
- <ul class="toc">
- <li><a href="#intro-cube">1.1 A Data Cube vocabulary</a></li>
- <li><a href="#intro-rdf">1.2 RDF and Linked Data</a></li>
- <li><a href="#intro-sdmx">1.3 SDMX and related standards</a></li>
- <li><a href="#intro-scovo">1.4 Relationship to SCOVO</a></li>
- <li><a href="#intro-audience">1.5 Audience and scope</a></li>
- <li><a href="#intro-conventions">1.6 Document conventions</a></li>
- </ul>
- </li>
- <li><a href="#data-cubes">2. Data cubes</a>
- <ul class="toc">
- <li><a href="#cubes-model">2.1 The cube model - dimensions, attributes, measures</a></li>
- <li><a href="#cubes-slices">2.2 Slices</a></li>
- </ul>
- </li>
- <li><a href="#example">3. An example</a></li>
- <li><a href="#outline">4. Outline of the vocabulary</a></li>
- <li><a href="#dsd">5. Creating data structure definitions</a>
- <ul class="toc">
- <li><a href="#dsd-dimensions">5.1 Dimensions, attributes and measures</a></li>
- <li><a href="#dsd-cog">5.2 Content oriented guidelines</a></li>
- <li><a href="#dsd-example">5.3 Example</a></li>
- <li><a href="#dsd-dsd">5.4 ComponentSpecifications and DataStructureDefinitions</a></li>
- <li><a href="#dsd-mm">5.5 Handling multiple measures</a></li>
- </ul>
- </li>
- <li><a href="#datasets">6. Expressing datasets</a> </li>
- <ul class="toc">
- <li><a href="#dataset-basic">6.1 The datasets and observations</a></li>
- </ul>
- <li><a href="#slices">7. Slices</a> </li>
- <li><a href="#schemes">8. Concept schemes and code lists</a> </li>
- <li><a href="#metadata">9. DataSet metadata</a> </li>
- <ul class="toc">
- <li><a href="#metadata-categorization">9.1 Categorizing a data set</a></li>
- <li><a href="#metadata-publishers">9.2 Describing publishers</a></li>
- </ul>
- <li><a href="#acknowledgements">Acknowledgements</a></li>
- <li><a href="#references">References</a></li>
- <li><a href="#namespaces-used-appendix">Appendix 1: namespaces used in this document</a></li>
- <li><a href="#appendix-vocab-reference">Appendix 2: vocabulary reference</a></li>
-</ul>
-<hr>
+<section id="intro-cube">
+<h3>A Data Cube vocabulary</h3>
-<h2 id="introduction">1. Introduction</h2>
-
-<h3 id="intro-cube">1.1 A Data Cube vocabulary</h3>
<p>
Statistical data is a foundation for policy
prediction, planning and adjustments and
@@ -150,8 +87,11 @@
<li><a href="http://purl.org/dc/terms/">Dublin Core Terms</a> for
metadata</li>
</ul>
+</section>
-<h3 id="intro-rdf">1.2 RDF and Linked Data</h3>
+
+<section id="intro-rdf">
+<h3>RDF and Linked Data</h3>
<p><em>Linked data</em> is an approach to publishing data on the web, enabling
datasets to be linked together through references to common concepts.
@@ -182,8 +122,11 @@
for programmatic access.</li>
<li>It enables reuse of standardized tools and components.</li>
</ul>
+</section>
-<h3 id="intro-sdmx">1.3 SDMX and related standards</h3>
+
+<section id="intro-sdmx">
+<h3>SDMX and related standards</h3>
<p>The Statistical Data and Metadata Exchange (SDMX) Initiative
was organised in 2001 by seven international organisations (BIS,
@@ -223,8 +166,11 @@
terms are available separately for use along with the Data Cube
vocabulary.
</p>
+</section>
-<h3 id="intro-scovo">1.4 Relationship to SCOVO</h3>
+
+<section id="intro-scovo">
+<h3>Relationship to SCOVO</h3>
<p>The Statistical Core Vocabulary (SCOVO) <a href="#ref-scovo">[SCOVO]</a> is a lightweight
RDF vocabulary for expressing statistical data. Its relative
@@ -251,16 +197,22 @@
The design of the Data Cube vocabulary is informed by SCOVO,
and every SCOVO dataset can be re-expressed within the vocabulary.
</p>
+</section>
-<h3 id="intro-audience">1.5 Audience and scope</h3>
+
+<section id="intro-audience">
+<h3>Audience and scope</h3>
<p>This document describes the Data Cube vocabulary
It is aimed at people wishing to publish
statistical or other multi-dimension data in RDF.
Mechanics of cross-format translation from other
formats such as SDMX-ML will be covered elsewhere.</p>
+</section>
-<h3 id="intro-conventions">1.6 Document conventions</h3>
+
+<section id="intro-conventions">
+<h3>Document conventions</h3>
<p>
The names of RDF entities -- classes, predicates, individuals -- are
@@ -284,11 +236,17 @@
</ul>
<p>We also introduce the prefix <code>qb</code> for the Data Cube
namespace <a href="http://purl.org/linked-data/cube#">http://purl.org/linked-data/cube#</a>.</p>
+</section>
-<h2 id="data-cubes">2. Data cubes</h2>
+</section>
-<h3 id="cubes-model">2.1 The cube model - dimensions, attributes,
-measures</h3>
+
+<section id="data-cubes">
+<h2>Data cubes</h2>
+
+
+<section id="cubes-model">
+<h3>The cube model - dimensions, attributes, measures</h3>
<p>A statistical data set comprises a collection of observations made
at some points across some logical space. The collection can be characterized by
@@ -322,8 +280,11 @@
interpret the observed value(s). They enable specification of the units of
measures, any scaling factors and metadata such as the status
of the observation (e.g. <em>estimated</em>, <em>provisional</em>).</p>
+</section>
-<h3 id="cubes-slices">2.2 Slices</h3>
+
+<section id="cubes-slices">
+<h3>Slices</h3>
<p>It is frequently useful to group subsets of observations within a
dataset. In particular to fix all but one (or a small subset) of the
@@ -350,8 +311,12 @@
slices and do not give different names to particular types of slice but
extension vocabularies, such as SDMX-RDF, can easily add such
concept labels.</p>
+</section>
-<h2 id="example">3. An example</h2>
+</section>
+
+<section id="example">
+<h2>An example</h2>
<p>In order to illustrate the use of the data cube vocabulary we will
use a small demonstration
@@ -479,12 +444,17 @@
fixed for each slice. Such slices then show the variation in life expectancy across the
different regions, i.e. corresponding to the columns in the above tabular layout.</p>
+</section>
-<h2 id="outline">4. Outline of the vocabulary</h2>
+
+<section id="outline">
+<h2>Outline of the vocabulary</h2>
<img src="images/qb-fig1.png" />
- <h3>Vocabulary index</h3>
+<section id="index">
+<h3>Vocabulary index</h3>
+
<p><b>Classes:</b>
<a href='#ref_qb_Attachable'>qb:Attachable</a>
<a href='#ref_qb_AttributeProperty'>qb:AttributeProperty</a>
@@ -521,8 +491,13 @@
<a href='#ref_qb_structure'>qb:structure</a>
<a href='#ref_qb_subSlice'>qb:subSlice</a>
</p>
+</section>
-<h2 id="dsd">5. Creating data structure definitions</h2>
+</section>
+
+
+<section id="dsd">
+<h2>Creating data structure definitions</h2>
<p>A <code>qb:DataStructureDefinition</code> defines the structure of one or more
datasets. In particular, it defines the dimensions, attributes and measures
@@ -546,7 +521,8 @@
that structure once and then reuse it for each publication in the series. Consumers can then be
confident that the structure of the data has not changed.</p>
-<h3 id="dsd-dimensions">5.1 Dimensions, attributes and measures</h3>
+<section id="dsd-dimensions">
+<h3>Dimensions, attributes and measures</h3>
<p>The Data Cube vocabulary represents the dimensions, attributes and measures
as RDF properties. Each is an instance of the abstract <code>qb:ComponentProperty</code>
@@ -606,8 +582,10 @@
<p>Before illustrating the components needed for our running example, there is one more piece
of machinery to introduce, a reusable set of concepts and components based on SDMX.
</p>
+</section>
-<h3 id="dsd-cog">5.2 Content oriented guidelines</h3>
+<section id="dsd-cog">
+<h3>Content oriented guidelines</h3>
<p>The SDMX standard includes a set of <em>content oriented guidelines</em> (COG) <a href="#ref-cog">[COG]</a>
which define a
@@ -626,8 +604,11 @@
terms. However, when the concepts being expressed do match a COG concept it is recommended
that publishers should reuse the corresponding components and/or concept URIs to simplify comparisons
across data sets. Given this background we will reuse the relevant COG components in our worked example.</p>
+</section>
-<h3 id="dsd-example">5.3 Example</h3>
+
+<section id="dsd-example">
+<h3>Example</h3>
<p>Turning to our example data set then we can see there are three dimensions to represent
- time period, region (unitary authority) and sex of the population. There is a single
@@ -681,8 +662,11 @@
which corresponds to the topic of the Wikipedia page on "Years".</p>
<p>This covers the minimal components needed to define the structure of this data set.</p>
+</section>
-<h3 id="dsd-dsd">5.4 ComponentSpecifications and DataStructureDefinitions</h3>
+
+<section id="dsd-dsd">
+<h3>ComponentSpecifications and DataStructureDefinitions</h3>
<p>To combine the components into a specification for the structure of this
datasets we need to declare a <code>qb:DataStuctureDefinition</code>
@@ -738,8 +722,11 @@
are only useful within the scope of a particular DSD and so we have chosen the represent
them using blank nodes.
</p>
+</section>
-<h3 id="dsd-mm">5.5 Handling multiple measures</h3>
+
+<section id="dsd-mm">
+<h3>Handling multiple measures</h3>
<p>Our example data set is relatively simple in having a single observable (in this case "life expectancy")
that is being measured. In other data sets there can be multiple measures. These measures
@@ -758,6 +745,8 @@
<p>The data cube vocabulary permits either representation approach to be used though they cannot be mixed
within the same data set.</p>
+
+<section id="dsd-mm-obs">
<h4>Multi-measure observations</h4>
<p> This approach allows multiple observed values to be attached
@@ -795,7 +784,10 @@
the <em>unit of measure</em> for that measure) but that attachment applies to the whole data
set (indeed any data set using that measure property) and cannot vary for different observations.
For applications where this limitation is a problem then use the <em>measure dimension</em> approach.</p>
+</section>
+
+<section id="dsd-mm-dim">
<h4>Measure dimension</h4>
<p>This approach restricts observations to having a single measured value but allows
@@ -853,8 +845,15 @@
measures, those individual measures are used directly. The SDMX-in-RDF extension
vocabulary addresses the round-tripping of the SDMX primary measure by use of a
separate annotation on <code>sdmx:DataStructureDefinition</code>.</p>
+</section>
-<h2 id="datasets">6. Expressing data sets</h2>
+</section>
+
+</section>
+
+
+<section id="datasets">
+<h2>Expressing data sets</h2>
<p>A DataSet is a collection of statistical data that corresponds to a given data structure definition.
The data in a data set can be roughly described as belonging to one of the following kinds:</p>
@@ -883,7 +882,9 @@
External metadata is described in <a href="#metadata">section 9</a>.</dd>
</dl>
-<h3 id="dataset-basic">6.1 Data sets and observations</h3>
+
+<section id="dataset-basic">
+<h3>Data sets and observations</h3>
<p>A resource representing the entire data set is created and typed as <code>qb:DataSet</code> and
linked to the corresponding data structure definition via the <tt>qb:structure</tt> property.</p>
@@ -984,8 +985,13 @@
must have a complete set of dimension values, along with all the measure values. If the
set is structured by using slices then further abbreviation is possible, as discussed
in the next section.</p>
-
-<h2 id="slices">7. Slices</h2>
+</section>
+
+</section>
+
+
+<section id="slices">
+<h2>Slices</h2>
<p>Slices allow us to group subsets of observations together. This not intended
to represent arbitrary selections from the observations but uniform slices
@@ -1131,8 +1137,11 @@
in general flat representations are recommended to simplify data consumption.
Some tool chains may support (dynamic or static) generation flattened representations from
abbreviated data sets.</p>
-
-<h2 id="schemes">8. Concept schemes and code lists</h2>
+</section>
+
+
+<section id="schemes">
+<h2>Concept schemes and code lists</h2>
<p>The values for dimensions within a data set must be unambiguously
defined. They may be typed values (e.g. <code>xsd:dateTime</code> for time instances)
@@ -1221,8 +1230,11 @@
The use of <code>skos:narrower</code> makes it possible to declare new
concept schemes which extend an existing scheme by adding additional aggregation layers on top.
All items are linked to the scheme via <code>skos:inScheme</code>.</p>
+</section>
-<h2 id="metadata">9. DataSet metadata</h2>
+
+<section id="metadata">
+<h2>DataSet metadata</h2>
<p>DataSets should be marked up with metadata to support discovery, presentation and
processing. Metadata such as a display label (<code>rdfs:label</code>),
@@ -1230,7 +1242,9 @@
are common to most resources. We recommend use of Dublin Core Terms
for representing the key metadata annotations commonly needed for DataSets.</p>
-<h3 id="metadata-categorization">9.1 Categorizing a data set</h3>
+
+<section id="metadata-categorization">
+<h3>Categorizing a data set</h3>
<p>Publishers of statistics often categorize their data sets into different statistical
domains, such as <em>Education</em>, <em>Labour</em>, or <em>Transportation</em>.
@@ -1260,8 +1274,11 @@
<p>where <code>eg:Wales</code> is a <code>skos:Concept</code> drawn from an appropriate controlled
vocabulary for places.</p>
+</section>
-<h3 id="metadata-publishers">9.2 Describing publishers</h3>
+
+<section id="metadata-publishers">
+<h3>Describing publishers</h3>
<p>The organization that publishes a dataset should be recorded as part of the dataset metadata.
Again we recommend use of the Dublin Core term <code>dcterms:publisher</code> for this.
@@ -1278,55 +1295,15 @@
<p>Note that the SDMX extension vocabulary supports further description of
publication pipelines (data flows, reporting taxonomies, maintainers, provision agreements.</p>
-
-<h2 id="acknowledgements">Acknowledgements</h2>
-
-<p>This work is based on a collaboration that was initiated in a
-workshop on Publishing statistical datasets in SDMX and the semantic
-web, hosted by ONS in Sunningdale, United Kingdom in February 2010 and
-continued at the ODaF 2010 workshop in Tilburg. The authors would like
-to thank all the participants at those workshops for their input into
-this work but especially Arofan Gregory for his patient
-explanations of SDMX and insight in the need and requirements
-for a core Data Cube representation.</p>
-
-<p>The authors would also like to thank John Sheridan for his comments,
-suggestions and support for this work.</p>
-
-<h2 id="references">References</h2>
-
-<dl>
- <dt id="ref-OLAP">[OLAP]</dt>
- <dd>Online Analytical Processing Data Cubes, <a href="http://en.wikipedia.org/wiki/OLAP_cube">http://en.wikipedia.org/wiki/OLAP_cube</a></dd>
-
- <dt id="ref-linked-data">[LOD]</dt>
- <dd>Linked Data, <a href="http://linkeddata.org/">http://linkeddata.org/</a></dd>
+</section>
- <dt id="ref-rdf">[RDF]</dt>
- <dd>Resource Description Framework, <a href="http://www.w3.org/RDF/">http://www.w3.org/RDF/</a></dd>
-
- <dt id="ref-scovo">[SCOVO]</dt>
- <dd>The Statistical Core Vocabulary, <a href="http://sw.joanneum.at/scovo/schema.html">http://sw.joanneum.at/scovo/schema.html</a> <br />
- SCOVO: Using Statistics on the Web of data, <a href="http://sw-app.org/pub/eswc09-inuse-scovo.pdf">http://sw-app.org/pub/eswc09-inuse-scovo.pdf</a>
-</dd>
-
- <dt id="ref-skos">[SKOS]</dt>
- <dd>Simple Knowledge Organization System, <a href="http://www.w3.org/2004/02/skos/">http://www.w3.org/2004/02/skos/</a></dd>
+</section>
- <dt id="ref-cog">[COG]</dt>
- <dd>SDMX Contnent Oriented Guidelines, <a href="http://sdmx.org/?page_id=11">http://sdmx.org/?page_id=11</a></dd>
-
- <dt id="ref-admingeo">[OS-GEO]</dt>
- <dd>Ordnance Survey Administrative Geography Ontology v1, <a href="http://www.ordnancesurvey.co.uk/ontology/v1/AdministrativeGeography.rdf">http://www.ordnancesurvey.co.uk/ontology/v1/AdministrativeGeography.rdf</a></dd>
- <dt id="ref-org">[ORG]</dt>
- <dd>An Organization Ontology, <a href="http://www.epimorphics.com/public/vocabulary/org.html">http://www.epimorphics.com/public/vocabulary/org.html</a></dd>
+<section id="namespaces-used-appendix" class="appendix">
+<h2>Namespaces used in this document</h2>
-</dl>
-
-<h2 id="namespaces-used-appendix">Appendix 1: namespaces used in this document</h2>
-
-<table class="spare-table" style="margin-left: 5ex;">
+<table class="spare-table">
<thead> <tr>
<th>prefix</th>
<th>namespace URI</th>
@@ -1376,10 +1353,16 @@
</tr>
</tbody>
</table>
+</section>
-<h2 id="appendix-vocab-reference">Appendix 2: vocabulary reference</h2>
- <h3>DataSets </h3>
+<section id="vocab-reference" class="appendix">
+<h2>Vocabulary reference</h2>
+
+
+<section id="reference-datasets">
+<h3>DataSets</h3>
+
<dl class='vocab_reference'>
<dt id="ref_qb_DataSet">
@@ -1391,7 +1374,12 @@
</dt>
<dd>Represents a collection of observations, possibly organized into various slices, conforming to some common dimensional structure.</dd>
</dl>
- <h3>Observations </h3>
+</section>
+
+
+<section id="reference-observations">
+<h3>Observations</h3>
+
<dl class='vocab_reference'>
<dt id="ref_qb_Observation">
@@ -1423,7 +1411,12 @@
</dt>
<dd>indicates a observation contained within this slice of the data set</dd>
</dl>
- <h3>Slices </h3>
+</section>
+
+
+<section id="reference-slices">
+<h3>Slices</h3>
+
<dl class='vocab_reference'>
<dt id="ref_qb_Slice">
@@ -1453,7 +1446,11 @@
</dt>
<dd>Indicates a narrower slice which has additional fixed dimensional values, for example a time-series slice might a subSlice of a slice which spans both time and geographic area</dd>
</dl>
- <h3>Dimensions, Attributes, Measures </h3>
+</section>
+
+
+<section id="reference-components">
+<h3>Dimensions, Attributes, Measures</h3>
<dl class='vocab_reference'>
<dt id="ref_qb_Attachable">
@@ -1497,7 +1494,11 @@
</dt>
<dd>Superclass of all coded ComponentProperties</dd>
</dl>
- <h3>Reusable general purpose component properties </h3>
+</section>
+
+
+<section id="reference-component-properties">
+<h3>Reusable general purpose component properties</h3>
<dl class='vocab_reference'>
<dt id="ref_qb_measureType">
@@ -1509,7 +1510,11 @@
</dt>
<dd>Generic measure dimension, the value of this dimension indicates which measure (from the set of measures in the DSD) is being given by the obsValue (or other primary measure)</dd>
</dl>
- <h3>Data Structure Definitions </h3>
+</section>
+
+
+<section id="reference-dsd">
+<h3>Data Structure Definitions</h3>
<dl class='vocab_reference'>
<dt id="ref_qb_DataStructureDefinition">
@@ -1539,7 +1544,11 @@
</dt>
<dd>indicates a component specification which is included in the structure of the dataset</dd>
</dl>
- <h3>Component specifications - for qualifying component use in a DSD </h3>
+</section>
+
+
+<section id="reference-compspec">
+<h3>Component specifications - for qualifying component use in a DSD</h3>
<dl class='vocab_reference'>
<dt id="ref_qb_ComponentSpecification">
@@ -1638,7 +1647,11 @@
</dt>
<dd>An alternative to qb:componentProperty which makes explicit that the component is a measure dimension</dd>
</dl>
- <h3>Slice definitions </h3>
+</section>
+
+
+<section id="reference-slice-definitions">
+<h3>Slice definitions</h3>
<dl class='vocab_reference'>
<dt id="ref_qb_SliceKey">
@@ -1668,7 +1681,11 @@
</dt>
<dd>indicates a slice key which is used for slices in this dataset</dd>
</dl>
- <h3>Concepts </h3>
+</section>
+
+
+<section id="reference-concepts">
+<h3>Concepts</h3>
<dl class='vocab_reference'>
<dt id="ref_qb_concept">
@@ -1691,6 +1708,61 @@
</dt>
<dd>gives the code list associated with a CodedProperty</dd>
</dl>
+</section>
+
+</section>
+
+
+<section id="acknowledgements" class="appendix">
+<h2>Acknowledgements</h2>
+
+<p>This work is based on a collaboration that was initiated in a
+workshop on Publishing statistical datasets in SDMX and the semantic
+web, hosted by ONS in Sunningdale, United Kingdom in February 2010 and
+continued at the ODaF 2010 workshop in Tilburg. The authors would like
+to thank all the participants at those workshops for their input into
+this work but especially Arofan Gregory for his patient
+explanations of SDMX and insight in the need and requirements
+for a core Data Cube representation.</p>
+
+<p>The authors would also like to thank John Sheridan for his comments,
+suggestions and support for this work.</p>
+</section>
+
+
+<section class="appendix">
+<h2 id="references">References</h2>
+
+<dl>
+ <dt id="ref-OLAP">[OLAP]</dt>
+ <dd>Online Analytical Processing Data Cubes, <a href="http://en.wikipedia.org/wiki/OLAP_cube">http://en.wikipedia.org/wiki/OLAP_cube</a></dd>
+
+ <dt id="ref-linked-data">[LOD]</dt>
+ <dd>Linked Data, <a href="http://linkeddata.org/">http://linkeddata.org/</a></dd>
+
+ <dt id="ref-rdf">[RDF]</dt>
+ <dd>Resource Description Framework, <a href="http://www.w3.org/RDF/">http://www.w3.org/RDF/</a></dd>
+
+ <dt id="ref-scovo">[SCOVO]</dt>
+ <dd>The Statistical Core Vocabulary, <a href="http://sw.joanneum.at/scovo/schema.html">http://sw.joanneum.at/scovo/schema.html</a> <br />
+ SCOVO: Using Statistics on the Web of data, <a href="http://sw-app.org/pub/eswc09-inuse-scovo.pdf">http://sw-app.org/pub/eswc09-inuse-scovo.pdf</a>
+</dd>
+
+ <dt id="ref-skos">[SKOS]</dt>
+ <dd>Simple Knowledge Organization System, <a href="http://www.w3.org/2004/02/skos/">http://www.w3.org/2004/02/skos/</a></dd>
+
+ <dt id="ref-cog">[COG]</dt>
+ <dd>SDMX Contnent Oriented Guidelines, <a href="http://sdmx.org/?page_id=11">http://sdmx.org/?page_id=11</a></dd>
+
+ <dt id="ref-admingeo">[OS-GEO]</dt>
+ <dd>Ordnance Survey Administrative Geography Ontology v1, <a href="http://www.ordnancesurvey.co.uk/ontology/v1/AdministrativeGeography.rdf">http://www.ordnancesurvey.co.uk/ontology/v1/AdministrativeGeography.rdf</a></dd>
+
+ <dt id="ref-org">[ORG]</dt>
+ <dd>An Organization Ontology, <a href="http://www.epimorphics.com/public/vocabulary/org.html">http://www.epimorphics.com/public/vocabulary/org.html</a></dd>
+
+</dl>
+</section>
+
</body>
</html>
--- a/data-cube/respec-config.js Thu Feb 09 23:28:24 2012 +0100
+++ b/data-cube/respec-config.js Fri Feb 10 19:14:41 2012 +0000
@@ -34,7 +34,17 @@
{ name: "Richard Cyganiak", url: "http://richard.cyganiak.de/", company: "DERI, NUI Galway", companyURL: "http://www.deri.ie/" },
{ name: "Dave Reynolds", company: "Epimorphics Ltd", companyURL: "http://www.epimorphics.com/" },
],
-//@@@ <dd>Jeni Tennison (<a href="http://www.jenitennison.com/blog/">TSO</a>)</dd>
+ otherContributors: {
+ "Previous editor": [
+ { name: "Jeni Tennison",
+ url: "http://www.jenitennison.com/blog/",
+ company: "TSO",
+ companyURL: "http://www.tso.co.uk/"
+ //mailto: "xx@yy",
+ //note: "xxx",
+ },
+ ],
+ },
// authors, add as many as you like.
// This is optional, uncomment if you have authors as well as editors.
@@ -58,40 +68,6 @@
// Team Contact.
wgPatentURI: "",
maxTocLevel: 3,
- preProcess: [ preProc ]
+ //preProcess: [ preProc ]
//alternateFormats: [ {uri: "diff-20110507.html", label: "diff to previous version"} ],
};
-
-function updateExample(doc, content) {
- // perform transformations to make it render and prettier
- content = content.replace(/<!--/, '');
- content = content.replace(/-->/, '');
- content = doc._esc(content);
- content = content.replace(/\*\*\*\*([^*]*)\*\*\*\*/g, '<span class="diff">$1</span>') ;
- return content ;
-}
-
-function updateDTD(doc, content) {
- // perform transformations to
- // make it render and prettier
- content = '<pre class="dtd">' + doc._esc(content) + '</pre>';
- content = content.replace(/!ENTITY % ([^ \t\r\n]*)/g, '!ENTITY <span class="entity">% $1</span>');
- content = content.replace(/!ELEMENT ([^ \t$]*)/mg, '!ELEMENT <span class="element">$1</span>');
- return content;
-}
-
-function updateSchema(doc, content) {
- // perform transformations to
- // make it render and prettier
- content = '<pre class="dtd">' + doc._esc(content) + '</pre>';
- content = content.replace(/<xs:element\s+name="([^&]*)"/g, '<xs:element name="<span class="element" id="schema_element_$1">$1</span>"') ;
- return content;
-}
-
-function updateTTL(doc, content) {
- // perform transformations to
- // make it render and prettier
- content = '<pre class="sh_sourceCode">' + doc._esc(content) + '</pre>';
- content = content.replace(/@prefix/g, '<span class="sh_keyword">@prefix</span>');
- return content;
-}