Intelligent User Interfaces Research Group Directed by: Frank Shipman

Visual Knowledge Builder (VKB): Supporting Personal Collections  Problem: information tasks require a combination of location, comprehension, and modification Current systems have emphasized the location of information (e.g. search engines, portals)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 contentThere 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 cuesSpatial hypertext expresses inter-document relationships via visual and spatial cues Users develop personal visual languages during the course of their activitiesUsers 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.The system can recognize parts of the visual language and interpretation to support the user’s task. Frank Shipman VKB

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

Experience with VKB Use VKB Project Management Conference Planning Writing Papers & Creating Presentations

VITE : Manipulating Structured Information in a Visual Workspace  Problem: computers generate/require lots of structured information but people prefer natural representations Incomplete representation – formal representations abstract real contentIncomplete representation – formal representations abstract real content Insufficient intermediate representation – formal representations miss transient states during problem solvingInsufficient 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 parsingTwo-ways: (1) visualization and (2) visual parsing Editable visualization and mappingEditable visualization and mapping Direct manipulation of content in the workspaceDirect manipulation of content in the workspace Haowei Hsieh VITE

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

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

GRC: Graphical Requirements Collector   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 J. Michael Moore GRC

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

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

MASH / WARP Luis Francisco-Revilla MASH  Problem: information needs to be adapted based on the use context Information systems can employ multiple models in order to adapt content and presentation.Information systems can employ multiple models in order to adapt content and presentation. Conflict may occur as different models propose contradicting suggestions.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.

Architectural Framework Spatial Hypermedia Platform Spatial Parser Spatial Analyzer Spatial Transformer Composites Metrics Transformations Behaviors M1M1 M2M2 MnMn Spatial Hypermedia Generator Contents Dynamic Adaptive Generative Interactive Models 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. Ontology of Adaptations Object Abstraction MASH SpaceDynamic/Static Dimensions Homogeneous/Heterogeneous ObjectComposite Atomic Document Relationship Association Quality Scope Explicit Implicit Absolute Relative Extra-space Intra-space

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. WARP is 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. The spatial structure provides a useful definition of context that facilitates the adaptation of the document. MASH