Added Simon's text on informationally equivalent distributions

dcat/index.html

@@ -1670,6 +1670,9 @@ <h3>Class: Distribution</h3>
 
         <div class="note">
             <p> Examples of distributions include a CSV file, a netCDF file, a JSON document, or a data-cube, files made accessible according to different profiles, such as XML or JSON schemas or ShEx or SHACL expressions.</p>
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+            <p>In some cases all distributions of a dataset will be fully informationally equivalent, in the sense that lossless transformations between the representations are possible. An example would be different serializations of an RDF graph using RDF/XML, Turtle, N3, JSON-LD. However, in other cases the distributions might have different levels of fidelity to the underlying data. For example, a graphical representation alongside a CSV file. The question of whether different representations can be understood to be distributions of the same dataset is use-case specific, so the judgement is the responsibility of the provider. </p>
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             <p>
                 The scope of <code>dcat:Distribution</code> here is narrower than in DCAT-2014 [[?VOCAB-DCAT-20140116]], where it also included APIs and feeds.
                 Data catalogues designed using DCAT-2014 therefore used instances of type <code>dcat:Distribution</code> to describe data distribution services.