This preview shows page 1-2-3-4-5-6-7-8-9-10-11-12-13-95-96-97-98-99-100-101-102-103-104-105-106-107-108-190-191-192-193-194-195-196-197-198-199-200-201-202 out of 202 pages.
Basic Lessons in ORA and Automap 2009 Kathleen M Carley Mike Bigrigg Jeff Reminga John Storrick Matt DeReno and Dave Columbus July 2008 CMU 09 117 Institute for Software Research School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 Center for the Computational Analysis of Social and Organizational Systems CASOS Technical Report 1 1 This work was supported by the ONR N00014 06 1 0104 the AFOSR for Computational Modeling of Cultural Dimensions in Adversary Organization MURI the ARL for Assessing C2 structures the DOD and the NSF IGERT 9972762 in CASOS Additional support was provided by CASOS and ISRI at Carnegie Mellon University The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies either expressed or implied of the National Science Foundation the Department of Defense and the Office of Naval Research the Army Research Labs the Air Force Office of Sponsored Research or the U S government Key Words DNA ORA Automap Dynamic Network Analysis MetaNetwork Social Network Analysis ii Abstract ORA is a network analysis tool that detects risks or vulnerabilities of an organization s design structure The design structure of an organization is the relationship among its personnel knowledge resources and tasks entities These entities and relationships are represented by the Meta Matrix Measures that take as input a Meta Matrix are used to analyze the structural properties of an organization for potential risk ORA contains over 100 measures which are categorized by which type of risk they detect Measures are also organized by input requirements and by output ORA generates formatted reports viewable on screen or in log files and reads and writes networks in multiple data formats to be interoperable with existing network analysis packages In addition it has tools for graphically visualizing Meta Matrix data and for optimizing a network s design structure ORA uses a Java interface for ease of use and a C computational backend The current version ORA1 2 software is available on the CASOS website http www casos ece cmu edu projects ORA index html iii iv Table of Contents 1 Basic Lessons in ORA 1 Reports 2 2 Belief Report 2 2 1 BELIEFS REPORT 7 2 2 Analysis for the belief network Agent x belief 8 3 Capacity Report 11 3 1 Overall Capability and Needs 11 3 2 Highest Requirements 11 3 3 Requirements 13 4 13 5 Capacity Report 14 5 1 Overall Capability and Needs 14 5 2 Requirements 15 6 Key Entity Report Basic 17 6 1 Main Dialog Box 17 6 2 The Reports 18 6 3 Output Options 18 7 Key Entity Report Other Options 20 7 1 General Transformation 20 7 2 Remove Entities Options 22 7 3 Partition Options 23 7 4 Summary 23 8 Mental Model Reports 24 8 1 Mental Model Reports Bibliography 24 9 24 10 Tasks 25 11 Contextual Menus 25 12 Contextual Menus Multi Files 27 13 Creating a Network from an Excel Spreadsheet 31 14 Hovering 33 15 Info Tab Network 34 16 Info Tab NodeSet 36 17 Running an Intelligence Report 37 17 1 Who are the critical actors 37 17 2 INTELLIGENCE REPORT 39 17 3 KEY ACTORS 39 17 4 Emergent Leader cognitive demand 39 17 5 In the Know total degree centrality 39 v 17 6 Number of Cliques clique count 40 17 7 Most Knowledge row degree centrality 40 17 8 Most Resources row degree centrality 41 17 9 Leader of Strong Clique eigenvector centrality 41 17 10 Potentially Influential betweenness centrality 42 17 11 Connects Groups high betweenness and low degree 42 17 12 Unique Task Assignment task exclusivity 43 17 13 Special Expertise knowledge exclusivity 43 17 14 Special Capability resource exclusivity 44 17 15 Workload actual based on knowledge and resource 44 17 16 KEY KNOWLEDGE 45 17 17 KEY RESOURCES 45 17 18 KEY LOCATIONS 45 17 19 III What do we know about an actor of interest 48 17 20 1 Visualize information about a selected actor 48 17 21 2 Visualize an actor s sphere of influence 49 17 22 3 Run a Sphere of Influence Report 50 17 23 SPHERE OF INFLUENCE REPORT 51 17 24 Sphere of Influence Analysis for agent ahmed ghailani 51 17 25 Size Statistics 51 17 26 Attributes 52 17 27 Exclusive Connections 52 17 28 Most Similar Node 52 17 29 Top Measures 52 17 30 Measure Value Range 53 17 31 53 17 32 Resource Analysis Section 54 17 33 IV What are the connections between two actors of interest 55 17 34 V What is the immediate impact of a particular agent on the network 56 17 35 VI What happens to the network when certain entities are removed 57 18 Create a New Meta Network 65 18 1 Delete an existing node 66 18 2 Merge two nodes 67 19 Performing a View Network Over Time Analysis 67 19 1 Performing the Over Time Analysis 70 19 2 Example Slider Position 1 71 19 3 Example Slider Position 2 72 19 4 Example Slider Position 3 72 19 5 WTC Event Node Detail 1 1996 73 19 6 WTC Event Node Detail 2 1997 74 19 7 Summary of Lesson 75 vi 20 Performing the View Measures Over Time Analysis 76 20 1 Performing the View Measures Over Time Analysis 76 20 2 Interpreting The Results After Performing View Measures Over Time Analysis 77 21 Renaming 79 21 1 Renaming Meta Networks Meta Nodes and Networks 79 22 Running An Over Time Analysis 79 22 1 Overview Over Time Viewer 79 23 Lessons 83 24 Lesson 1 ORA Overview 83 24 1 Overview of ORA Interface 83 24 2 Loading a meta network into ORA 83 24 3 The Visualizer 84 25 Lesson 2 Creating A New Meta Network 86 25 1 Lesson 101 86 25 2 lessons 201 207 86 25 3 lessons 301 86 26 101 Examine Your Data 87 26 1 General Thoughts 87 26 2 What s in a Node Class 88 26 3 Agents Who 88 26 4 Locations Where 90 26 5 Events When 91 26 6 Tasks How 91 26 7 Knowledge What 92 26 8 Resources What 92 26 9 Networks 93 26 10 Difference between the two MetaNetworks 93 27 201 Excel and CSV 94 27 1 Your first NodeSet 94 27 2 Your first Network 95 27 3 The rest of the NodeSets and Networks 96 27 4 Saving as CSV files 97 28 202 Import into ORA 98 28 1 Starting a new Meta Network 98 28 2 Adding to the new Meta Network 100 29 203 Attributes 103 29 1 The Special Attribute Title 103 29 2 Adding other Attributes and Values 108 30 204 Modifying a Meta Network 110 30 1 Step 1 Adding a New Node 110 30 2 Step 2 Importing the Attributes 113 vii 31 32 205 Working with SubSets 115 206 Attribute Columns 117 32 1 Replacing an Attribute Column 117 33 207 Updating Your Data Files 119 33 1 Saving Your Network Data 119 33 2 Saving Your Attribute Data …
View Full Document
Unlocking...