svn commit: r1614865 - /jena/site/trunk/content/documentation/csv/index.mdtext

[jpz6311whu]

Author: jpz6311whu
Date: Thu Jul 31 11:52:26 2014
New Revision: 1614865

URL: http://svn.apache.org/r1614865
Log:
change documentation encoding for JENA-625

Modified:
    jena/site/trunk/content/documentation/csv/index.mdtext

Modified: jena/site/trunk/content/documentation/csv/index.mdtext
URL: 
http://svn.apache.org/viewvc/jena/site/trunk/content/documentation/csv/index.mdtext?rev=1614865&r1=1614864&r2=1614865&view=diff
==============================================================================
--- jena/site/trunk/content/documentation/csv/index.mdtext (original)
+++ jena/site/trunk/content/documentation/csv/index.mdtext Thu Jul 31 11:52:26 
2014
@@ -7,7 +7,7 @@ It includes getting the right architectu
 
 This module involves the basic mapping of CSV to RDF using a fixed algorithm, 
including interpreting data as numbers or strings.
 
-Suppose we have a CSV file located in ¡°file:///c:/town.csv¡±, which has one 
header row, two data rows:
+Suppose we have a CSV file located in “file:///c:/town.csv”, which has one 
header row, two data rows:
 
     Town,Population
     Southton,123000
@@ -17,8 +17,8 @@ As RDF this might be viewable as:
  
     @prefix : <file:///c:/town.csv#> .
     @prefix csv: <http://w3c/future-csv-vocab/> .
-    [ csv:row 1 ; :Town "Southton" ; :Population  
¡°123000¡±^^http://www.w3.org/2001/XMLSchema#int ] .
-    [ csv:row 2 ; :Town "Northville" ; :Population  
¡°654000¡±^^http://www.w3.org/2001/XMLSchema#int  ] .
+    [ csv:row 1 ; :Town "Southton" ; :Population  
“123000”^^http://www.w3.org/2001/XMLSchema#int ] .
+    [ csv:row 2 ; :Town "Northville" ; :Population  
“654000”^^http://www.w3.org/2001/XMLSchema#int  ] .
  
 or without the bnode abbreviation:
  
@@ -26,10 +26,10 @@ or without the bnode abbreviation:
     @prefix csv: <http://w3c/future-csv-vocab/> .
     _:b0  csv:row 1 ;
           :Town "Southton" ;
-          :Population ¡°123000¡±^^http://www.w3.org/2001/XMLSchema#int .
+          :Population “123000”^^http://www.w3.org/2001/XMLSchema#int .
     _:b1  csv:row 2 ;
           :Town "Northville" ;
-          :Population ¡°654000¡±^^http://www.w3.org/2001/XMLSchema#int.
+          :Population “654000”^^http://www.w3.org/2001/XMLSchema#int.
           
 Each row is modeling one "entity" (here, a population observation). 
 There is a subject (a blank node) and one predicate-value for each cell of the 
row. 
@@ -37,7 +37,7 @@ Row numbers are added because it can be 
 Now the CSV file is viewed as a graph - normal, unmodified SPARQL can be used. 
 Multiple CSVs files can be multiple graphs in one dataset to give query across 
different data sources.
  
-We can use the following SPARQL query for ¡°Towns over 500,000 people¡± 
mentioned in the CSV file:
+We can use the following SPARQL query for “Towns over 500,000 people” 
mentioned in the CSV file:
  
     SELECT ?townName ?pop {
       GRAPH <file:///c:/town.csv> {