--- a/glossary/index.html Mon Mar 18 09:15:44 2013 +0000
+++ b/glossary/index.html Tue Mar 19 14:02:02 2013 -0400
@@ -127,8 +127,7 @@
<section>
<h4>curl</h4>
-A command line client for retrieving machine readable content. To see exactly how human and machine readable content works, try this exercise. Wikipedia has an interesting page about the color <a href="http://wikipedia.org/wiki/Red" target="_blank">Red</a>. DBpedia allows you to get the structured content listed on the Wikipedia page for "Red" [<a href="http://wikipedia.org/wiki/Red">http://wikipedia.org/wiki/Red</a>] by changing "wiki" to "data" and appending the appropriate file extension.
-<pre>$ curl -L http://dbpedia.org/data/Red.ttl</pre>
+A command line client to retrieve any data over a wide variety of protocols, including machine readable RDF.
</section>
<section>
@@ -153,7 +152,7 @@
<section >
<h4>Data Cloud</h4>
-Data cloud, also called the <a href="http://richard.cyganiak.de/2007/10/lod/" target="_blank">Linked Data Cloud</a>, is a visual representation of datasets published as Linked Data. Using metadata generated by directoies, including CKAN, the project records datasets by domain. The Linked Data Cloud has doubled in size every 10 months since 2007 and as of late 2012 consists of more than 300 data sets from various domains, including geography, media, government and life sciences, according the [<a href="http://lod-cloud.net/state/">State of the LOD Cloud</a>], website and visualizations maintained by C. Bizer, A. Jentzsch, R. Cyganiak. The original data owners/stewards publish one third of the data contained in the Linked Open Data Cloud, while third parties publish 67%. Many academic institutions republish data from their respective governments as <a href="#linked-data">Linked Data</a>, often enhancing the representation in the process.
+Data cloud, also called the <a href="http://richard.cyganiak.de/2007/10/lod/" target="_blank">Linked Data Cloud</a>, is a visual representation of datasets published as Linked Data. Using metadata generated by directories, including CKAN, the project records datasets by domain. The Linked Data Cloud has doubled in size every 10 months since 2007 and as of late 2012 consists of more than 300 data sets from various domains, including geography, media, government and life sciences, according the [<a href="http://lod-cloud.net/state/">State of the LOD Cloud</a>], website and visualizations maintained by C. Bizer, A. Jentzsch, R. Cyganiak. The original data owners/stewards publish one third of the data contained in the Linked Open Data Cloud, while third parties publish 67%. Many academic institutions republish data from their respective governments as <a href="#linked-data">Linked Data</a>, often enhancing the representation in the process.
</section >
<section >
@@ -340,7 +339,14 @@
<section>
<h4>Machine Readable Data</h4>
-Machine readable gets 2-stars on the <a href="#5-star-linked-data">5-star Linked Data scale</a>. Many open data developers routinely use screen-scrapping techniques to parse machine readable content. Publishing and consuming 4-star and 5-star Linked Data is preferable in terms of access and re-use. Anything less gives Web developers more work modeling and transforming data. By creating and publishing 5-star Linked Data, you are increasing the ability of search engines, and thus humans, to find, access and re-use information.</section>
+<p>Machine readable gets 2-stars on the <a href="#5-star-linked-data">5-star Linked Data scale</a>. While some open data developers use screen-scrapping techniques to parse machine readable content, using 4-star or 5-star Linked Data is preferable in terms of provenance and ease of reuse. Anything less than 4-star data gives Web developers more work modeling and transforming data. By creating and publishing Linked Data, you are increasing the ability of search engines, and thus humans, to find, access and re-use information.
+</p>
+<p>
+To see how a Linked Data representation yields both a human and machine readable version simultaneously, try this exercise. Wikipedia has an interesting page about the color <a href="http://wikipedia.org/wiki/Red" target="_blank">Red</a>. DBpedia allows you to get the structured content listed on the Wikipedia page for "Red" [<a href="http://wikipedia.org/wiki/Red">http://wikipedia.org/wiki/Red</a>] by changing "wiki" to "data" and appending the appropriate file extension.
+<pre>$ curl -L http://dbpedia.org/data/Red.ttl</pre>
+Thus, you've seen how the same data can be viewed in human and machine readable format from the same page.
+</p>
+</section>
<section>
<h4>Message</h4>
@@ -404,6 +410,16 @@
</section>
<section>
+<h4>Persistent Uniform Resource Locator</h4>
+A persistent uniform resource locator (PURL) is a <a href="uniform-resource=locator">uniform resource locator</a> (URL) that is used to redirect to the location of the requested web resource. PURLs redirect HTTP clients using HTTP status codes. PURLs are used to curate the URL resolution process, thus solving the problem of transitory URIs in location-based URI schemes like HTTP. Thus, a user of a PURL always uses the same Web address, even though the resource in question may have moved. Note, an expansion of PURL that is sometimes found is "permanent uniform resource locator" however that is incorrect as it does not capture the key concept of <em>persistence</em>.
+</section>
+
+<section>
+<h4>Persistent Identifier Scheme</h4>
+A persistent identifier scheme is a mechanmism for resolution of virtual resources. <a href="http://en.wikipedia.org/wiki/Persistent_uniform_resource_locator">Persistent Uniform Resource Locator (PURLs)</a> implement one form of persistent identifier for virtual resources. PURLs are valid URLs and their components must map to the URL specification. The scheme part tells a computer program, such as a Web browser, which protocol to use when resolving the address. The scheme used for PURLs is generally HTTP. Other persistent identifier schemes include <a href="http://en.wikipedia.org/wiki/Digital_object_identifier" target="_blank">Digital Object Identifiers (DOIs)></a>, <a href="http://en.wikipedia.org/wiki/LSID" target="_blank">Life Sciences Identifiers (LSIDs)</a> and <a href="http://en.wikipedia.org/wiki/Info:" target="_blank">INFO URIs</a>. All persistent identification schemes provide unique identifiers for (possibly changing) virtual resources, but not all schemes provide curation opportunities.
+</section>
+
+<section>
<h4>Predicate</h4>
The predicate is the second part of an <a href="#rdf">RDF</a> statement and defines the property for the subject of the statement. In the context of RDF, a predicate modifies the <a href="#subject">Subject</a> of an <a href="#rdf">RDF</a> Statement. Predicate refers to a piece of knowledge expressed formally in the field of AI. Inspired from work in predicate calculus, (also called predicate logic, first order logic), the predicate of a sentence can be thought of as the verb.
</section>