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Visualization of Uncertainty in the Common Operating Picture

Visualization of Uncertainty in the Common Operating Picture. WorkGroup 4:. Justin Hollands David Baar Thomas Porathe Liesa Lapinski. Harvey Smallman Szymon Stachniak Nada Ivanovic Carolyn MacGregor. Overview: Uncertainty Visualization. Problem

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Visualization of Uncertainty in the Common Operating Picture

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  1. Visualization of Uncertainty in the Common Operating Picture WorkGroup 4: Justin Hollands David Baar Thomas Porathe Liesa Lapinski Harvey Smallman Szymon Stachniak Nada Ivanovic Carolyn MacGregor

  2. Overview: Uncertainty Visualization • Problem • Decision-makers need to know what is not known as much as what is known • Existing displays imply a ground truth that can mislead • Objective • Produce a COP that allows users to tailor their information needs on uncertainty to rapidly changing ROEs • Approach • Develop a taxonomy of task-relevant uncertainties • Design and evaluate display concepts to query and visualize them Benefits • Better informed, flexible decision making

  3. Displays implicitly adopt uncertainty criteria Problem: Displays and “Ground Truth” Identity attributes: all certain Location & temporal: certain Identity attributes: category certain, platform/affiliation not Location & temporal: certain Risky Criteria More Conservative

  4. Our Approach • Develop and evaluate explicit visualisation concepts to • Make uncertainty, underlying assumptions and display criteria explicit • Query uncertainty levels of tracks • Directly manipulate the consequences of choosing different uncertainty levels • Support decision-making needs by tailoring uncertainty levels to extant ROEs.

  5. Creating a Taxonomy of Uncertainty • The different types of uncertainty inherent in visualizing the COP • Uncertainty inherent in display technology • Display / data sampling (spatial, temporal) • Uncertainty in the data displayed • Conflicting / missing attributes for track ID • Spatial and temporal sensor uncertainties • Uncertainty in the perceptual response • Imprecision (e.g., with viewing angle). Weber fractions.

  6. Existing representations of Uncertainty • Limited array of existing methods for displaying uncertainty • Track ID • Icon in icon (e.g. AADC threat coding) • Disintegrated attribute representations (CROs) • Spatial uncertainty • Spatial envelopes (e.g. sonar, meterology displays) • Blobology (dispersion/distribution of troops across space – USMC) • Temporal • ???

  7. Design & Control Issues • What are appropriate designs for customizable displays for levels of uncertainty? • How might querying of information be integrated with displays of target uncertainty? • Should the customizable displays differ depending on the target? • Global or track-specific queries? • Integration of temporal information? • Making the uncertainty information decision-relevant (response plan management)? • What are the trade-offs between displaying uncertainty and display clutter?

  8. Direct manipulation interface 100% Spatial Certainty (10%) 0% (70%) 0% Certainty of ID 100%

  9. Direct manipulation interface Time??? 100% Spatial Certainty (50%) 0% (70%) 0% Certainty of ID 100%

  10. 100% M29 Spatial Certainty 0% 0% (70%) 100% 0% 100% Certainty of ID (95%) Direct manipulation interface

  11. (95%) Direct manipulation interface 100% Spatial Certainty 0% (95%) 0% Certainty of ID 100%

  12. (95%) Drill-down for assumptions etc 100% Spatial Certainty 0% (95%) 0% Certainty of ID 100%

  13. Priorities 1… 2… 3… 4… (updated) Assumptions 1 … 2… 3… 4... (updated) • Control of • Decision Spatial Certainty Rules of Engagement (updated) Sensor Management/ Intel Management (updated) (95%) 0% Certainty of ID 100% (95%) Integration with associated displays 100% 0%

  14. (95%) Integration with response management 100% M29 Spatial Certainty 0% 0% (70%) 100% 0% 100% Certainty of ID Shoot Query

  15. Interpretation of Uncertainty • How does viewpoint contribute to the operator’s assessment of uncertainty? • Line of sight (occluded regions, exact location along the line of sight, cartesian location in 3D space) • Distance estimation (relative vs actual • Spatial resolution of display (aka blobology) • What is the relationship between available time to decide and assessment of uncertainty as a useful decision-making variable in order to act? • How should temporal representation be conveyed? • What are the parameters of uncertainty that might be considered by an intelligent agent? • Should uncertainty be displayed by an intelligent/automated agent?

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