diff --git a/models/Application_examples/Correlation_and_Fusion_Process_with_Data_Governance.mp b/models/Application_examples/Correlation_and_Fusion_Process_with_Data_Governance.mp
index 6c10f07429e9fe937431f0f87cd70e30fe1b9eda..51d14e9037e94f0c9b8189c55416c4f07d98820f 100644
--- a/models/Application_examples/Correlation_and_Fusion_Process_with_Data_Governance.mp
+++ b/models/Application_examples/Correlation_and_Fusion_Process_with_Data_Governance.mp
@@ -1,52 +1,78 @@
-/* Applied Data Governance Framework Model	
-created by F Watson 8/20/2021 
-    
-    Purpose: 
-    To model AIS reporting data flows showing updated data path behaviors with the application of a data governance framework 
-    
-    Description:
-    Models the data flow from sensors all the way to the human analyst at a tactical location incorporating a data governance framework.
-    
-     Details
-     AIS_Sensor: represents an example AIS GPS SENSOR
-     Aggregation_Service: Represents a local AIS Aggregator like a "Radar" system or local AIS Broadcast
-     Global_Distribution_Mechanism: Receives data from multiple aggregation services, coalates the data, and rebroadcasts the data globally.
-
-     Source A: Represents raw AIS tracks that have not been modified in any way prior to dissemination
-     Source B: Represents raw AIS tracks grouped into geographic areas for limited broadcast
-     Source C: Represents Custom filtering and combining of AIS tracks based on unique fields
-
-     Data Governance Framework applies evaluation rubric to data sources and only allows sources that are uncorrupted to be transmitted to the correlator.
-     The Data_Governance_Framework receivees sources, evaluates source corruption levels, applies a rubric evaluation, and transmits approved sources to the correlator function  
-    							  
-
-     Correlator functions: 		Receive_Source_Status 
-    					Process_Source_Status
+/* Model of Correlation and Fusion Process with Data Governance Framework
+
+Created by Frank Watson on the 20th of August, 2021.
+Edited by Pamela Dyer in September, 2021.
+
+Purpose: To model AIS reporting data flows showing updated 
+data path behaviors with the application of a data 
+governance framework.
+
+Description: Models the data flow from sensors all the way 
+to the human analyst at a tactical location incorporating 
+a data governance framework.
+
+    Details
+    AIS_Sensor: represents an example AIS GPS SENSOR
+    Aggregation_Service: Represents a local AIS Aggregator 
+        like a "Radar" system or local AIS Broadcast
+    Global_Distribution_Mechanism: Receives data from 
+        multiple aggregation services, coalates the data, 
+        and rebroadcasts the data globally.
+
+    Source A: Represents raw AIS tracks that have not been 
+        modified in any way prior to dissemination
+    Source B: Represents raw AIS tracks grouped into 
+        geographic areas for limited broadcast
+    Source C: Represents Custom filtering and combining 
+        of AIS tracks based on unique fields
+
+    Data Governance Framework applies evaluation rubric 
+    to data sources and only allows sources that are 
+    uncorrupted to be transmitted to the correlator.
+    The Data_Governance_Framework receives sources, 
+    evaluates source corruption levels, applies a rubric 
+    evaluation, and transmits approved sources to the 
+    correlator function.
+
+    Correlator functions: 		Receive_Source_Status 
+                        Process_Source_Status
     					Evaluate_Source_Status
 					Display_Correlated_Tracks
-     Analyst functions:  	   View_Correlated_Tracks
-				   Analyze_Tracks_Position_Accuracy
-				   Correct_Track_Positions
-
-    The events are representative of actual AIS data report flow to operational analysts, with the insertion of a data governance framework.  
-    
-    References:
-    
-    Example 49 Histogram showing number of traces with probabilities within certain intervals, from Auguston, M. "Monterey Phoenix 
-    System and Software Architecture and Workflow Modeling Language Manual" 
-    (Version 4). 2020. Available online: https://wiki.nps.edu/display/MP/Documentation
-
-    Example 40. A global report is assembled from the set of all available event traces, from Auguston, M. "Monterey Phoenix 
-    System and Software Architecture and Workflow Modeling Language Manual" 
-    (Version 4). 2020. Available online: https://wiki.nps.edu/display/MP/Documentation
-
-	Search terms: behavior, data correlation and fusion; probability, Type 1; data governance 
-    
-    Instructions:
-    Run for scope 1: 4 traces in < 1 sec
-  
-
-*/
+    Analyst functions:  	   View_Correlated_Tracks
+                    Analyze_Tracks_Position_Accuracy
+                    Correct_Track_Positions
+
+    The events are representative of actual AIS data report 
+    flow to operational analysts, with the insertion of a 
+    data governance framework.
+
+References:
+Watson, Frank. "Design Methodologies for 21st Century 
+    Battlefield Object Correlation and Fusion." NPS 
+    Master's Thesis, Monterey, CA: September 2021.
+
+Example 49. Histogram showing number of traces with 
+    probabilities within certain intervals, from Auguston, 
+    M. "Monterey Phoenix System and Software Architecture 
+    and Workflow Modeling Language Manual" (Version 4). 
+    2020. Available online: 
+    https://wiki.nps.edu/display/MP/Documentation
+
+Example 40. A global report is assembled from the set of 
+    all available event traces, from Auguston, M. 
+    "Monterey Phoenix System and Software Architecture 
+    and Workflow Modeling Language Manual" (Version 4). 
+    2020. Available online: 
+    https://wiki.nps.edu/display/MP/Documentation
+
+Search terms: behavior, data correlation and fusion; 
+probability, Type 1; data governance
+
+Instructions: Run for Scope 1.
+    Scope 1: 4 traces in less than 1 sec.
+
+==========================================================*/
+
 SCHEMA Correlation_and_Fusion_Process_with_Data_Governance