1. Representing Uncertainty, Unknowns and Dynamics of Social Networks NX-Workshop on Social Network Analysis and Visualization for Public Safety 18 – 19 October 2005

2. Presentation Organization For each of the three topics: Topic introduction and rough description Concrete examples of relevant social networks. Representation options Optional: listed in terms of preference

3. Network Development Phenomenon / Thing / Situation Analyst’s Understanding Display Choice of Representation Audience Understanding

4. Representation Orthogonality It is often important to represent unknowns, uncertainty and dynamics using visual attributes that are orthogonal to the visual attributes already used for other purposes.

5. Generic Network Variables (of an Epidemic) Constraints Rules Nodes Location Node type Symbology Open/Closed Node ID Input/output property Links Capacity Weight Strength Direction Availability Type of traffic Location Route Identification (Unique) The medium Thresholds and changes Traffic Flow Path Routing Topology Symmetric/asymmetric Boundaries Layout Hierarchical Tree Topology evolution in time and space Logical/physical Redundancy Partially connected graph Protocols Networks interconnections Location Open/Closed Layers Hierarchy

6. Unknowns - Definition An unknown variable is a variable of which no information is available as to (type 1) its expected value or (type 2) its existence. Type 1 can be represented. e.g. unknown variables in a mathematical equation. Type 2, an “unknown unknown”, is difficult to deal with although there are transforms which could denote lack of information. e.g. “You do not know that you are missing that variable.”

7. Constraints Rules Nodes Location Node type Open/Closed Node ID Input/output property Links Capacity Weight Direction Availability Type of traffic The medium Thresholds and changes Traffic Path Topology Symmetric/asymmetric Boundaries Layout Hierarchical Tree Topology evolution in time and space Partially connected graph Protocols Networks interconnections Location Open/Closed Layers Hierarchy Unknowns – Network Variables

8. Unknowns – Visualization Labeling Unknowns (e.g. ???) Ghosting Demarcated Emptiness Black Boxes ? Ben Carl Bob ? ?

9. Uncertainty - Definition An “uncertain” variable is a variable whose exact value is not known but unlike a unknown value, a (partial?) probability distribution for potential values exists.

10. Uncertainty – Visualization Colour Pattern Shape Edge highlighting Secondary/selection highlighting Movement/vibration/animation speed/animation style Haze/blurriness/ transparency Line thickness Textual labels Spatial Probability Distribution for Link Path Spatial Probability Distribution for Node Position

11. Uncertainty – Network Variables Constraints Rules Nodes Location Node type Input/output property Links Capacity Weight Direction Availability Type of traffic Location Route Thresholds and changes Traffic Flow Path Routing Topology Symmetric/asymmetric Boundaries Layout Redundancy Partially connected graph Networks interconnections Location

12. Dynamics - Definition The change of network structure (i.e. add/remove node/links) or the change of network element attributes with time.

13. Constraints Rules Nodes Location Node type Open/Closed Input/output property Links Capacity Weight Direction Availability Location Route Traffic Flow Path Topology Boundaries Topology evolution in time and space Partially connected graph Networks interconnections Location Open/Closed Dynamics – Network Variables

14. Dynamics - Visualization Animated movement / color Color Blinking Fade Appear/Disappear Temporary brightness Zoom to a new element (selective attention) Exploratory methods (sliders) Node Movement Structure Change (removal)