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MSR Data Mountain

MSR Data Mountain. Written by: George Roberston, Mary Czerwinski, Kevin Larson, Daniel C. Robbins, David Thiel, and Maarten van Dantzich. Using Spatial Memory for Data Management. Presentation by: Krishnan Ram Capstone Fall 2004. Key Questions. What is Spatial Cognition?

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MSR Data Mountain

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  1. MSR Data Mountain Written by: George Roberston, Mary Czerwinski, Kevin Larson, Daniel C. Robbins, David Thiel, and Maarten van Dantzich Using Spatial Memory for Data Management Presentation by: Krishnan Ram Capstone Fall 2004

  2. Key Questions • What is Spatial Cognition? • What is the Data Mountain? • How does the Data Mountain work? • How have users responded to the Data Mountain concept? • What can this idea contribute to the Capstone project?

  3. Real-World Spatial Cognition • Can be thought as how we perceive objects in space and their relationships to one another • Examples • Remembering where we left our glasses • Distinguishing our current body orientation with respect to the environment. • What do I need to do to get where I need to go?

  4. Spatial Cognition in a Virtual Setting • Can 3D Human Spatial Cognition be applied in a virtual environment?

  5. Spatial Cognition in a Virtual Setting • Can 3D Human Spatial Cognition be applied in a virtual environment? • The answer is yes. Research has shown that adding borders, paths, directional cues, and audio cues make navigating 3D space easier.

  6. Document Management Systems • This concept can be applied to Document Management Systems. • A DMS is a workspace or environment where one can manipulate and view multiple documents in a common space.

  7. Document Management Systems • 2-Dimensional • Windows Explorer • IE Favorites • 3-Dimensional • Web Forager • Xerox PARC Information Visualizer

  8. Example of 2D System:Windows Explorer

  9. Example of 3D System:Web Forager

  10. Data Mountain • What is the Data Mountain project?

  11. Data Mountain • What is the Data Mountain project? • It is a Document Management System that uses a 3D virtualized environment with a 2D interaction scheme. • 3D perception used to maximize amount of documents represented (due to 3D space) with minimum cognitive load.

  12. Reducing Cognitive Load • Our pre-attentive ability to recognize spatial relationships based on simple depth cues (occlusion, perspective views) makes it possible to place documents at a distance (thus reducing space used on desktop) without consciously thinking about it.

  13. Reducing Cognitive Load • We judge many spatial relationships in the real world without implicitly thinking about it. • Creating a virtual 3D world can allow us to utilize implicit cognition to help identify where documents were placed. • We often remember the approximate position of where we last placed something.

  14. Description • Documents can be placed in any arbitrary position on an inclined plane (hence the name Data “Mountain”) with a simple interaction tool such as the mouse. • Documents appear in thumbnail views on the plane. • User has complete control where they place a document. • One fixed viewpoint. • Increase amount of data in viewing field by making it 3D.

  15. Description • The current Data Mountain prototype is being used and tested as an alternative to the Favorites feature in Microsoft’s Internet Explorer.

  16. Internet Explorer • IE uses a 2D DMS to keep track of a user’s favorites internet websites. • Each site is shown as purely text, displaying the URL or title of the website. • Favorites can be grouped into a hierarchy depending on the user’s preference.

  17. Data Mountain Features • Favorite websites are stored as thumbnail images. • The thumbnails can be placed anywhere on the Data Mountain using the mouse. • Grouping is done by location. • Title of page is shown as a pop up when mouse hovers over it. • Page Avoidance Behavior (explained later)

  18. View of Data Mountain Desktop With 100 Websites

  19. Sensory Cues Aiding in Spatial Cognition • Visual Cues • Perspective views • Occlusion • Landmarks on the planar surface • Shadows cast by thumbnails • Auditory Cues • Dynamic sound effects

  20. Data Mountain Interaction • Documents stored as thumbnail icons on 3D plane. • When a thumbnail is clicked the document moved into the preferred viewing position

  21. Data Mountain Interaction • To aide in searching, pop ups of the title of each thumbnail are shown whenever the mouse passes over them • Pop ups are instantaneous (no delay) and a halo is outlined around the thumbnail it refers to • Thumbnails are moved around by simply dragging them with the mouse

  22. Movement: Page Avoidance Behavior • What happens to the other pages when you move a thumbnail through their common space?

  23. Movement: Page Avoidance Behavior • What happens to the other pages when you move a thumbnail through their common space (collisions)? • Three design methods explored • Do nothing • ‘Tall Grass’ Simulation • Page Avoidance Behavior

  24. User Study • A user study was conducted to determine the effectiveness of the Data Mountain • The study compared the Internet Explorer’s Favorites mechanism and the Data Mountain’s document management system

  25. Method • Thirty-two IE users were separated into 3 groups • Group 1:Stored & retrieved web pages using IE Favorites • Group 2: Stored & retrieved web pages using Data Mountain (version 1) • Group 3: Stored & retrieved web pages using Data Mountain (version 2)

  26. Method • Each participant were told to store 100 web pages in any organizational structure they wanted using IE Favorites, DM1 or DM2 (depending on their group) • Then participants were shown 1 of 4 different retrieval cues and asked to find the corresponding website within a 2 min period. • 25 trials for each cuing condition.

  27. Results • Four main variables measured • Reaction time: Amount of time taken to retrieve website • Incorrect Retrievals: Number of incorrect pages selected before finding the correct one • Failed attempts: Participant went over 2 mins • Participants Ratings of software

  28. Retrieval Cues

  29. Results

  30. Results

  31. Results

  32. Results Scale: 1-Disagree 5- Agree

  33. Conclusion • It is apparent that spatial memory playing a significant role in 3D virtual environments. • The incorporation of multiple sensory cues in the Data Mountain increased the reaction time and decreased the number of failed attempts and incorrect retrievals.

  34. Contributions to the Capstone • In the Virtualized Classroom project the individual items (videostream, audio control, slides, Mimio, instructor) should be customizable so the student can place them in such a position that is familiar to them and so reduce the cognitive load by using implicit spatial memory cues.

  35. Contributions to the Capstone • In the Augmented New York project, virtualized spatial memory plays a large role. The virtualized city and the real city must have some common spatial features so that the user can easily distinguish where they are and find where they want to go.

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