Added perspectives on provenance
authorSimon@Sherbet.dcs.kcl.ac.uk
Thu, 29 Sep 2011 13:54:30 +0100
changeset 414 428dcafc38d4
parent 413 5e9633cfbdef
child 415 2975ca449df3
child 516 e3ac35e2969f
Added perspectives on provenance
Changed PIDM to Prov-DM
primer/Primer.html
--- a/primer/Primer.html	Wed Sep 28 18:22:09 2011 -0400
+++ b/primer/Primer.html	Thu Sep 29 13:54:30 2011 +0100
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <html><head> 
-        <title>Provenance Model Primer</title>
+        <title>Prov Model Primer</title>
         <meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
         <!--
           === NOTA BENE ===
@@ -20,7 +20,7 @@
                 specStatus:           "ED",
           
                 // the specification's short name, as in http://www.w3.org/TR/short-name/
-                shortName:            "PIDM-Primer",
+                shortName:            "Prov-Primer",
  
                 // if your specification has a subtitle that goes below the main
                 // formal title, define it here
@@ -51,6 +51,8 @@
                 // editors, add as many as you like
                 // only "name" is required
                 editors:  [
+                    { name: "Yolanda Gil", url: "http://www.isi.edu/~gil/",
+                        company: "Information Sciences Institute, University of Southern California, US" },
                     { name: "Simon Miles", url: "http://www.inf.kcl.ac.uk/~simonm",
                         company: "King's College London, UK" },
                 ],
@@ -83,7 +85,7 @@
     </head>
     <body>
         <section id="abstract">
-            <p>This document aims to provide an intuitive guide to the Provenance Interchange Data Model,
+            <p>This document aims to provide an intuitive guide to the Prov Data Model,
                 with worked examples.</p>
 
             <p>
@@ -93,37 +95,51 @@
 
         <section> 
             <h2>Introduction</h2>
-            <p>The Provenance Interchange Data Model (PIDM) is used to describe the provenance of things, i.e.
-                how something came to be, from what sources, its history, etc. As such, PIDM data consists
+            <p>The Prov Data Model (Prov-DM) is used to describe the provenance of things, i.e.
+                how something came to be, from what sources, its history, etc. As such, Prov-DM data consists
                 of assertions about the past. These assertions are not assessments, e.g. as to something's
                 authenticity, but the plain facts from which such assessments might be derived.</p>
 
             <p>This guide aims to ease the adoption of the standard by providing:</p>
             <ul>
-                <li>An intuitive explanation of how PIDM models provenance.</li>
-                <li>Worked examples that can be followed to produce your own PIDM data.</li>
+                <li>An intuitive explanation of how Prov-DM models provenance.</li>
+                <li>Worked examples that can be followed to produce your own Prov-DM data.</li>
                 <li>Answers to frequently asked questions regarding how the model should be applied.</li>
             </ul>
         </section>
 
         <section>
-            <h2>Intuitive overview of PIDM</h2>
+            <h2>Intuitive overview of Prov-DM</h2>
 
-            <p><i>This section provides an intuitive explanation of the concepts in PIDM.
+            <p><i>This section provides an intuitive explanation of the concepts in Prov-DM.
                     As with the rest of this document, it should be treated as a starting point for understanding the model, and not normative in itself.
-                    The model specification provides the precise definitions and constraints to be followed in using PIDM.</i></p>
+                    The model specification provides the precise definitions and constraints to be followed in using Prov-DM.</i></p>
 
             <section>
+                <h2>Provenance</h2>
+
+                <p>Provenance has many meanings depending on what one is interested with regards to the object or resource in question.  Different people may have different perspectives, focusing on different types of information that might be captured in a provenance record.</p>
+
+                <p>One perspective might focus on entity-centered provenance, that is, what entities were involved in generating or manipulating the information in question.  Examples of entities include author, editor, publisher, curator, etc.</p>
+
+                <p>A second perspective might be one to focus on document-centered provenance, by tracing the origins of portions of a document to other documents. An example is referring to other news sources, quoting statistics from reports by some government or non-government agencies, etc.</p>
+
+                <p>A third perspective one might take is on process-centered provenance, capturing the actions and steps taken to generate the information in question.   (e.g., a data transformation, an edit, etc.).  An example is the records of execution of processes as workflows of web services.</p>
+
+            </section>
+
+                    
+            <section>
                 <h3>Provenance as data</h3>
-                <p>Describes a common pattern of production of PIDM data, e.g. the asserter being software
+                <p>Describes a common pattern of production of Prov-DM data, e.g. the asserter being software
                     enacting the process that it is asserting about, to clarify who might be using the model
                     and in what context.</p>
             </section>
 
             <section>
-                <h3>Perspective on the world</h3>
+                <h3>Prov-DM perspective on the world</h3>
 
-                <p>A brief and intuitive description of the way of thinking about the world when modelling it in PIDM.
+                <p>A brief and intuitive description of the way of thinking about the world when modelling it in Prov-DM.
                     In particular, this should contrast with other things users of provenance models may commonly have in mind,
                     such as Dublin Core-style attribution metadata or lab management system logs of closed, well-defined experiments.</p>
 
@@ -137,7 +153,7 @@
 
                 <h3>Entities, attributes and perspectives</h3>
 
-                <p>An intuitive overview of how to think about entities and their defining attributes in PIDM.</p>
+                <p>An intuitive overview of how to think about entities and their defining attributes in Prov-DM.</p>
 
             </section>
 
@@ -158,14 +174,14 @@
         <section>
             <h2>Worked Examples</h2>
 
-            <p>In the following sections, we show how PIDM can be used to model 
+            <p>In the following sections, we show how Prov-DM can be used to model 
                 provenance in specific examples.</p>
 
             <p>We include examples of how the formal ontology 
-                can be used to represent the PIDM assertions as RDF triples.
+                can be used to represent the Prov-DM assertions as RDF triples.
                 These are shown using the Turtle notation. In 
                 the latter depictions, the namespace prefix <b>po</b> denotes 
-                terms from the PIDM ontology, while <b>ex1</b>, <b>ex2</b>, etc. 
+                terms from the Prov ontology, while <b>ex1</b>, <b>ex2</b>, etc. 
                 denote terms specific to the example.</p>
 
             <p>We also provide a representation of the examples in the Abstract
@@ -176,7 +192,7 @@
                 <h3>News article example, part 1</h3>
 
                 <p>Charlie has published an article he has written as a web page,
-                    and wishes to make available PIDM data describing the history of that page.
+                    and wishes to make available Prov-DM data describing the history of that page.
                     He considers expressing that he was the article's publisher and that its content draws on a data set made available by the government.</p>
 
                 <p>First, he identifies the entities, agents, and process executions present in the scenario.
@@ -186,13 +202,13 @@
                     and the government data set on which the article was based.
                     Finally, there is one agent that both wrote and publishes the article, himself.</p>
 
-                <p>If encoded using the PIDM ontology, we create identifiers for each, and declare their type:</p>
+                <p>If encoded using the Prov ontology, we create identifiers for each, and declare their type:</p>
                 <blockquote>
-                    ex1:webpage1  a  po:Entity .<br/>
-                    ex1:unpublishedArticle1  a  po:Entity .<br/>
-                    ex1:dataSet1  a  po:Entity .<br/>
-                    ex1:published1  a  po:ProcessExecution .<br/>
-                    ex1:charlie  a  po:Agent .<br/>
+                    ex1:webpage1  a  prov:Entity .<br/>
+                    ex1:unpublishedArticle1  a  prov:Entity .<br/>
+                    ex1:dataSet1  a  prov:Entity .<br/>
+                    ex1:published1  a  prov:ProcessExecution .<br/>
+                    ex1:charlie  a  prov:Agent .<br/>
                 </blockquote>
 
                 <p>The entities, which includes the agent, are distinguished by their attributes.
@@ -213,11 +229,11 @@
                     He expresses the fact that the article draws on, was derived from, the data set.
                     Finally, he asserts that he published the article, i.e. controlled the publishing process execution.</p>
                 <blockquote>
-                    ex1:webpage1  po:wasGeneratedBy  ex1:published1 .<br/>
-                    ex1:published1  po:used  ex1:unpublishedArticle1 .<br/>
-                    ex1:unpublishedArticle  po:wasGeneratedBy  ex1:wrote1 .<br/>
-                    ex1:unpublishedArticle1  po:wasDerivedFrom  ex1:dataSet1 .<br/>
-                    ex1:published1  po:wasControlledBy  ex1:charlie .<br/>
+                    ex1:webpage1  prov:wasGeneratedBy  ex1:published1 .<br/>
+                    ex1:published1  prov:used  ex1:unpublishedArticle1 .<br/>
+                    ex1:unpublishedArticle  prov:wasGeneratedBy  ex1:wrote1 .<br/>
+                    ex1:unpublishedArticle1  prov:wasDerivedFrom  ex1:dataSet1 .<br/>
+                    ex1:published1  prov:wasControlledBy  ex1:charlie .<br/>
                 </blockquote>
 
             </section><section>