The Visual Knowledge Builder: A Second Generation Spatial Hypertext Frank M. Shipman III Haowei Hsieh Preetam Maloor J. Michael Moore

Why Spatial Hypertext? Lowers user’s effort of expression Lets Users express categories and interrelationships through Visual Similarity and co-location of information objects

Challenges for Spatial Hypertext The difficulty of interpreting changing visualizations The visualization interfering with visual source information The Inability to express cross-space interrelations The lack of means for expressing publishable information spaces The Inability to display media other than text in the workspace

Areas of Emphasis in VKB Improved support for visual expression and presentation Easier Inclusion of and Interaction with information from other applications Implicit visual types for improved structure recognition

Visual Expression and Presentation Borders of objects can be assigned colors Flexibility in Textual expression: change font size, style, typeface, and color Display images in the workspace

Integrating Information Files available via Local disk or network can be dragged from file browsers to VKB URLs can be dragged into VKB Cutting and pasting text into objects

Implicit Visual Types The Spatial Parser used in both VIKI and VKB recognizes structures implicit in the layout of objects in the workspace using each object’s position, size and type

Navigational Links in VKB Local links: connect an object to another object/collection/location in a collection Global Links: connects to information outside of the Spatial Hypertext Historical Links: An author can navigate the reader through both the space and time of a Hypertext

Applications Note taking, Writing, Project Management, and conference organization Collecting, organizing, and visually coding objects

Semantics Happen: Knowledge Building in Spatial Hypertext Frank M. Shipman III Haowei Hsieh Preetam Maloor J. Michael Moore Raghu Akkapeddi

Why Knowledge Representation? Knowledge based Hypertext became less famous with the emergence of web: HTML did not include useful facilities for more formal representation A lot of effort has gone to aid in use and sharing of knowledge but authoring the knowledge is not considered

Suggestions Suggestions are something offered for consideration. Classes of Suggestion: Task Assistance: MS Office Assistant Tool Assistance: Educate the User about processes and features available in the Tool

Issues With Suggestion Work Efficiency: reduction of cognitive load and time savings Notification: Either proactive or Reactive Distraction: Degree of distraction to the User Trust: User’s trust Control: When providing user assistance is control

VKB Suggestion Manager Notification: As Suggestions are generated they are presented by sliding a bar in the VKB Workspace (Fig 1) Suggestion Interface: When users choose to see the details it will open in a new window Suggestion Manager Interface: History of all suggestions for VKB are presented in a table (Fig 4) – Users can go back and deal with suggestions when they decide it is appropriate

Computation of Suggestions Spatial Analysis: Taking the layout and visual properties of the symbols in the workspace Textual Analysis: Calculates the relevance of a key phrase to the document Temporal Analysis: History data enables a temporal analysis of the workspace to look for patterns in the evolution of the workspace

Suggestion Types Type Suggestions Attribute Suggestions Placement Suggestions Relationship Suggestions Cleanup/Consolidation Suggestions

User Evaluation VKB Suggestion Manager and Microsoft Office Assistant: Effectiveness of both were Similar While VKB Suggestion Manager was less distracting