Topic Landscape

The Topic Landscape organizes a large amount of evolving material based on a basic principle of information design:

The navigation mechanisms should be a model of the topic being navigated.


This Topic Landscape is a framework for sharing and adding material about the overall scenario and developing the the demos around critical episodes within the storyline. More...



Description of content
  1. The intro section breaks down into a summary of the work (1.1), envisioning and the use of scenarios (1.2), our cognitive task analysis (1.3), and strategies behind the development of the Topic Landscape (1.4).

  2. The story framework captures the flow including the background, events that provide momentum and capture the demands of operations.
    This was the initial version demonstrated at the X-CTA kickoff meeting in 2004..

  3. The critical episodes provide a second level of structure within the story framework that can be developed to illustrate how sensor capabilities fit into and support MOUT.
    We provide a very initial breakdown of possible episodes, but I gather there was an active discussion of different possibilities that would fit into the technological advances different groups have been producing.

  4. The last part of the body of the Topic Landscape captures the deeper structure behind the story and episodes. This describes the general demands that make urban operations difficult and the generic patterns in cognitive work that are instantiated in this particular storyline. Some basic elements include:

    • The complicating factors that arise in situations to challenge decision making.
    • The the model of what makes urban operations difficult.
    • How the storyline represents basic patterns and findings in distributed cognitive work and coordinated activity.

    This is a critical part of scenario-based development as it provides a structure for organizing feedback and observations from using the scenario and how to generalize from what is just a case.

  5. The final section captures the eventual implications that result from using the scenario and the demos to learn more about the essential demands of urban operations and how new sensor and communications technologies can make an effective difference.