Intelligent User Interfaces Research Group Directed by: Frank Shipman

1. Intelligent User Interfaces Research GroupDirected by: Frank Shipman

2. Visual Knowledge Builder (VKB): Supporting Personal Collections Frank Shipman • Problem: information tasks require a combination of location, comprehension, and modification • Current systems have emphasized the location of information (e.g. search engines, portals) • There are few tools supporting the activity of comprehending and modifying the found content • Approach: Spatial hypertext • Spatial hypertext expresses inter-document relationships via visual and spatial cues • Users develop personal visual languages during the course of their activities • The system can recognize parts of the visual language and interpretation to support the user’s task. VKB

3. Expressing Relations Visually VKB provides: • A hierarchy of two-dimensional workspaces called collections for placing information • Easy manipulation ofvisual properties of information • Information objects pointing to external content • Attribute/value pairs for attaching metadata VKB

4. Experience with VKB Use ConferencePlanning Project Management Writing Papers & Creating Presentations VKB

5. VITE : Manipulating Structured Information in a Visual Workspace Haowei Hsieh • Problem: computers generate/require lots of structured information but people prefer natural representations • Incomplete representation –formal representations abstract real content • Insufficient intermediate representation –formal representations miss transient states during problem solving • Approach: 2-way mappings in a visual workspace • Two-ways: (1) visualization and (2) visual parsing • Editable visualization and mapping • Direct manipulation of content in the workspace VITE

6. Problem Solving in a Visual Workspace Visual mapping is created in the Mapping Designer. Structured information is rendered as information objects in the workspace. Users accomplish tasks by adjusting mapping designs and then manipulating information objects in the workspace. VITE

7. Generating Mappings with Ease • The Mapping Assistant generates mappings based on: • a brief description of the user’s task, • a statistical analysis of the data set, and • a mapping design knowledge-base combining results from the VITE evaluation with general graphic design principles. • The Mapping Assistant helps users generate initial mappings quickly so users can start working on the task right away. VITE

8. GRC: Graphical Requirements Collector J. Michael Moore • Problem: Software requirements elicitation • Questionnaires enable feedback from a large group but do not elicit rich design information. • Interviews and observations generate rich content but are expensive in time and money. • Approach: Collect design information from probable end-users through: • End-user graphical user interface mock-ups • Textual descriptions and rationales for the widgets and windows that they create GRC

9. Examples of End-user Mock-ups Below: Some users depend heavily on graphical organization. Above: Other users relied more on textual description. The text dialog explains the role of the “Design” button. GRC

10. Generating Design Information from Mock-ups Algorithms analyze spatial, textual, and temporal information to generate pattern-based views of design data to help construct domain models Main analysis interface provides access through: • Filtering mock-up components • Grouping components based on visual and textual similarity Term-frequency view of mock-up designs GRC

11. MASH / WARP Luis Francisco-Revilla • Problem: information needs to be adapted based on the use context • Information systems can employ multiple models in order to adapt content and presentation. • Conflict may occur as different models propose contradicting suggestions. • Approach: identifying mechanisms for dealing with conflicts • Deliver a flexible context-sensitive solution to this issue within the field of adaptive spatial hypermedia • MASH (Multi-model Adaptive Spatial Hypermedia) is a framework for dynamic and adaptive behaviors. MASH

12. Adaptive Transformations Spatial Transformer M1 M2 Metrics Spatial Analyzer Mn Models Dynamic Composites SpatialParser Interactive Behaviors Spatial Hypermedia Platform Atomic Dimensions Generative Contents Spatial Hypermedia Generator Object Composite Space Dynamic/Static Document Homogeneous/Heterogeneous Implicit Quality Explicit Relative Association Relationship Absolute Intra-space Scope Extra-space Architectural Framework Ontology of Adaptations Object Abstraction The MASH framework consists of three parts: a high-level abstraction of objects and relationships, a generic architectural framework, and a theoretical ontology of spatial adaptations. MASH

13. WARPis a first implementation of a MASH-based system. WARP can discover the implicit structure of a document as defined by the spatial relationships between objects. Adaptive mechanisms can hide or show different objects within the presentation in accordance to the user’s preferences. Conflict between multiple models can be resolved to fit relevant aspects of the use context, such as activity and situation. The spatial structure provides a useful definition of context that facilitates the adaptation of the document. MASH