--- a/data-cube/index.html	Thu Feb 23 19:50:52 2012 +0100
+++ b/data-cube/index.html	Thu Mar 01 17:45:30 2012 +0000
@@ -255,10 +255,10 @@
 <p>A statistical data set comprises a collection of observations made
 at some points across some logical space. The collection can be characterized by
 a set of dimensions that define what the observation applies to (e.g. time,
-area, population) along with metadata describing what has been
-measured (e.g. economic activity), how it was measured and how the
+area, gender) along with metadata describing what has been
+measured (e.g. economic activity, population), how it was measured and how the
 observations are expressed (e.g. units, multipliers, status). We can
-think of the statistical data set as multi-dimensional
+think of the statistical data set as a multi-dimensional
 space, or hyper-cube, indexed by those dimensions. This space is
 commonly referred to
 as a <em>cube</em> for short; though the name shouldn't be taken
@@ -337,13 +337,13 @@
       <td style="vertical-align: top;"><br>
       </td>
       <td colspan="2" rowspan="1"
- style="vertical-align: top; text-align: center; font-weight: bold;">2004-6<br>
+ style="vertical-align: top; text-align: center; font-weight: bold;">2004-2006<br>
       </td>
       <td colspan="2" rowspan="1"
- style="vertical-align: top; text-align: center; font-weight: bold;">2005-7<br>
+ style="vertical-align: top; text-align: center; font-weight: bold;">2005-2007<br>
       </td>
       <td colspan="2" rowspan="1"
- style="vertical-align: top; text-align: center; font-weight: bold;">2006-8<br>
+ style="vertical-align: top; text-align: center; font-weight: bold;">2006-2008<br>
       </td>
     </tr>
     <tr>
@@ -440,8 +440,8 @@
   </tbody>
 </table>
 
-<p>We can see that there are three dimensions - time period (averages over three year timespans?),
-  region, sex. Each observation represents the life expectancy for that population (the measure) and
+<p>We can see that there are three dimensions - time period (rolling averages over three year timespans),
+  region and sex. Each observation represents the life expectancy for that population (the measure) and
   we will need an attribute to define the units (years) of the measured values.</p>
 
 <p>An example of slicing the data would be to define slices in which the time and sex are
@@ -673,13 +673,13 @@
 <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>
+  dataset we need to declare a <code>qb:DataStuctureDefinition</code>
   resource which in turn will reference a set of <code>qb:ComponentSpecification</code> resources.
   The <code>qb:DataStuctureDefinition</code> will be reusable across other data sets with the same structure.</p>
 
 <p>In the simplest case the <code>qb:ComponentSpecification</code> simply references the
   corresponding <code>qb:ComponentProperty</code> (ususally using one of the sub properties
-  <code>qb:dimension</code>, <code>qb:measure</code> or <code>qb:attribute</code>. 
+  <code>qb:dimension</code>, <code>qb:measure</code> or <code>qb:attribute</code>). 
   However, it is also possible to qualify the
   component specification in several ways.</p>
 
@@ -694,8 +694,8 @@
     a so called <em>flattened</em> representation.
     This allows such observations to stand alone, so that a SPARQL query to retrieve the observation
     can immediately locate the attributes which enable the observation to be interpreted. However,
-    it is also permissible to attach attributes at other levels of the structure such as the
-    overall data set, an intervening slice or a specific Measure (in the case of multiple measures).
+    it is also permissible to attach attributes to the
+    overall data set, to an intervening slice or to a specific Measure (in the case of multiple measures).
     This reduces some of the redundancy in the encoding of the instance data. To declare such a 
     non-flat structure, the <code>qb:componentAttachment</code> property of the specification should
     reference the class corresponding to the attachment level (e.g. <code>qb:DataSet</code> for attributes
@@ -738,13 +738,14 @@
   multiple different performance indicators for each region) or quite different (e.g. a data set
   on trades might provide quantity, value, weight for each trade).</p>
   
-<p>There are two approaches to representing multiple measures. In the SDMX information model then each 
+<p>There are two approaches to representing multiple measures. In the SDMX information model, each 
   observation can record a single observed value. In a data set with multiple observations then we 
   add an additional dimension whose value indicates the measure. This is appropriate for applications
   where the measures are separate aggregate statistics. In other domains such as a clinical statistics
   or sensor networks then the term <em>observation</em> usually denotes an observation event which can include multiple
-  observed values.  Similarly in Business Intelligence applications and OLAP
-  then a single "cell" in the data cube will typically represent multiple facts about a single transaction.</p>
+  observed values.  Similarly in Business Intelligence applications and OLAP, a single "cell" in the data cube will 
+  typically contain values for multiple measures.
+</p>
   
 <p>The data cube vocabulary permits either representation approach to be used though they cannot be mixed
   within the same data set.</p>
@@ -1084,7 +1085,7 @@
 <p>Note that here we are still repeating the dimension values on the individual observations.
 This flattened representation means that a consuming application can still query 
 for observed values uniformly without having to first parse the data structure
-definition and search for slice definitions. If it is desired, these redundancy can be reduced
+definition and search for slice definitions. If it is desired, this redundancy can be reduced
 by declaring different attachment levels for the dimensions. For example:
 </p>
 <pre>
@@ -1149,9 +1150,9 @@
 
 <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)
-   or codes drawn from some for of code list. Similarly, many attributes
+   or codes drawn from some code list. Similarly, many attributes
    used in data sets represent coded values from some controlled term list rather 
-   than free text descriptions. In the Data Cube vocabulary such coded are
+   than free text descriptions. In the Data Cube vocabulary such codes are
    represented by URI references in the usual RDF fashion.</p>
  
 <p>Sometimes
@@ -1242,7 +1243,7 @@
 
 <p>DataSets should be marked up with metadata to support discovery, presentation and
 processing. Metadata such as a display label (<code>rdfs:label</code>),
-descriptive comment (<code>rdfs:comment</code>) and creation date (<code>dcterms:date)</code>
+descriptive comment (<code>rdfs:comment</code>) and creation date (<code>dcterms:date</code>)
 are common to most resources. We recommend use of Dublin Core Terms
 for representing the key metadata annotations commonly needed for DataSets.</p>
 
@@ -1253,7 +1254,7 @@
 <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>.
 We encourage use of <code>dcterms:subject</code> to record such a classification of
-an whole data set.
+a whole data set.
 The classification terms can include coarse grained classifications, such
 as the List of Subject-matter Domains from the SDMX Content-oriented Guidelines, 
 and fine grained classifications to support discovery of data sets.</p>
@@ -1298,7 +1299,7 @@
 </pre>
 
 <p>Note that the SDMX extension vocabulary supports further description of 
-  publication pipelines (data flows, reporting taxonomies, maintainers, provision agreements.</p>
+  publication pipelines (data flows, reporting taxonomies, maintainers, provision agreements).</p>
 </section>
 
 </section>
@@ -1435,7 +1436,7 @@
     (
     <code>qb:DataSet</code>
     -> 
-    <code>qb:Observation</code>
+    <code>qb:Slice</code>
   ) 
   </dt>
   <dd>Indicates a subset of a DataSet defined by fixing a subset of the dimensional values</dd>

--- a/data-cube/respec-config.js	Thu Feb 23 19:50:52 2012 +0100
+++ b/data-cube/respec-config.js	Thu Mar 01 17:45:30 2012 +0000
@@ -57,7 +57,8 @@
     wgURI:        "http://www.w3.org/2011/gld/",
 
     // name of the public mailing to which comments are due
-    wgPublicList: "public-gld-wg",
+    wgPublicList: "public-gld-comments",
+
 
     // URI of the patent status for this WG, for Rec-track documents
     // !!!! IMPORTANT !!!!