Merge pull request #47 from Jumpaku/master

fix typo: mnenomization -> mnemonization

README.md

@@ -35,7 +35,7 @@ A DSL (Domain Specifc Language) was desired that could be expressed in plain tex
 Schema rules are written for each column of the CSV file. Each set of column rules is then asserted against each row of the CSV file in turn. Each rule in the CSV Schema operates on the current context (e.g. defined Column and parsed Row), unless otherwise specified. Hopefully this makes the rules short and concise.
 
 * Streaming.
-Often the Metadata files that we receive are very large as they contain many records about a Collection which itself can be huge. The CSV Schema Language was designed with an eye to being able to write a Validation tool which could read the CSV file as a stream. Few steps require mnenomization of data from the CSV file, and where they do this is limited and should be easily optimisable to keep memory use to a minimum.
+Often the Metadata files that we receive are very large as they contain many records about a Collection which itself can be huge. The CSV Schema Language was designed with an eye to being able to write a Validation tool which could read the CSV file as a stream. Few steps require mnemonization of data from the CSV file, and where they do this is limited and should be easily optimisable to keep memory use to a minimum.
 
 * Sane Defaults.
 We try to do the right thing by default, CSV files and their bretheren (Tab Separated Values etc.) can come in many shapes and sizes, by default we parse CSV according to [RFC 4180](http://tools.ietf.org/html/rfc4180 "Common Format and MIME Type for Comma-Separated Values (CSV) Files"), of course we allow you to customize this behaviour in the CSV Schema.

csv-schema-1.0.html

@@ -229,7 +229,7 @@ <h2>Guiding Principles</h2>
                 </li>
                 <li>
                     <div class="principle">Stream Processing</div>
-                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnenomization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
+                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnemonization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
                 </li>
                 <li>
                     <div class="principle">Sane Defaults</div>

csv-schema-1.1.html

@@ -231,7 +231,7 @@ <h2>Guiding Principles</h2>
                 </li>
                 <li>
                     <div class="principle">Stream Processing</div>
-                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnenomization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
+                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnemonization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
                 </li>
                 <li>
                     <div class="principle">Sane Defaults</div>

csv-schema-1.2.html

@@ -232,7 +232,7 @@ <h2>Guiding Principles</h2>
                 </li>
                 <li>
                     <div class="principle">Stream Processing</div>
-                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnenomization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
+                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnemonization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
                 </li>
                 <li>
                     <div class="principle">Sane Defaults</div>

csv-schema.html

@@ -232,7 +232,7 @@ <h2>Guiding Principles</h2>
                 </li>
                 <li>
                     <div class="principle">Stream Processing</div>
-                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnenomization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
+                    <p>CSV files may be very large and so the CSV Schema Language was designed with concern for implementations, that although not required by the specification, MAY wish to read and process CSV data as a stream. Few operations require mnemonization of data from the CSV file, and where they do this is limited and should be optimisable to keep memory use to a minimum.</p>
                 </li>
                 <li>
                     <div class="principle">Sane Defaults</div>