Design Patterns Ubi Comp Patterns Evaluations Design Patterns
Design Patterns Ubi. Comp Patterns Evaluations Design Patterns in Ubiquitous Computing Eric Chung Jason I. Hong Jimmy Lin James A. Landay 1
Design Patterns Ubi. Comp Patterns Evaluations Introduction to Design Patterns • Patterns are developed to communicate common problems and solutions for designers in a discipline • First introduced by Christopher Alexander and his colleagues in the field of architecture 2
Design Patterns Ubi. Comp Patterns Evaluations Beer Hall Example • Problem: – Where can people sing and drink, and shout and drink, and let go of their sorrows? • Solution: – Somewhere in the community at least one big place where a few hundred people can gather, with beer and wine, music, and perhaps a halfdozen activities, so that people are continuously crisscrossing from one to another. 3
Design Patterns Ubi. Comp Patterns Evaluations Design Patterns for Ubiquitous Computing • Help designers create higher-quality designs faster by developing a pattern language for Ubi. Comp • Difficult to identify patterns because many design issues are still active areas of research • Difficult because certain problems do not have common solutions (have to resort to predictive patterns rather than descriptive) 4
Design Patterns Ubi. Comp Patterns Evaluations Identifying Patterns • We developed a criteria for identifying patterns: – Pattern should have at least one example in research and one example in industry • A list of over 60 Ubi. Comp patterns have been identified • Patterns are grouped into several important Ubi. Comp themes (e. g. , privacy) • A taxonomy of Ubi. Comp applications is also important to consider 5
Design Patterns Ubi. Comp Patterns Evaluations Themes Infrastructure Privacy Identification Manageability Personalization High-level Patterns Proxies for devices Balance of Power User Identity Bootstrap Ambiguity Service Handoff Chart of Ubi. Comp. Information Patterns Building Trust and Anonymous Base Credibility Negotiation & Resolution Relying on Multiple Sources Connections Effective Deployment Learning & Remembering Users Pseudo-Identity Social Situation Purpose Appropriate Scope of Access Scope of Control Appropriate Scope of Locality Scope of Time Partial Identification Medium-level Patterns Privacy Zones Active/Smart Floor Defaulting Data access via personalized devices Active Badge Fault Detection Bookmarks Choice Access Notice Low-Level Patterns Appropriate Retention Time Global Positioning RFID 6
Design Patterns Appropriate Levels of Attention Natural Interfaces Unobtrusive Prompting Subtle Reminders Ubi. Comp Patterns Anticipation Context. Sensitive I/O Active Teaching Point of Action Evaluations Global Data Discoverability Capture and Access Physical Space Chart of Ubi. Comp Patterns Learnability Experience Weiser’s Devices Physical-Virtual Associations Point of Information Appropriate Rate of Update Acceptance Practices & Etiquettes Location-based Services Capture (inch, foot, yard) Finding Locations Information Capture Touring Tracking Users Teleporting Ambiguity Follow-me Display Proximity-Based Tracking Accelerators World Model Active Map Wearable Computer Proximity-Based Tracking 7
Design Patterns Ubi. Comp Patterns Evaluations Applying Patterns • Exercise: Apply patterns to In/Out Board 8
Design Patterns Ubi. Comp Patterns Evaluations Applying Patterns • Exercise: Apply patterns to In/Out Board • Identify some relevant themes and their patterns: – Privacy: Appropriate Scope of Locality, Partial Identification (might only show first names), Choice, Access, Appropriate Retention Time – Identification: Active Badge, Smart Floor – Global Data: Active Map 9
Design Patterns Ubi. Comp Patterns Evaluations Evaluating the Patterns • Perform an experiment – Conditions: create two groups, one with patterns, one without – Task #1: ask the groups to evaluate an existing design – Task #2: ask the groups to prototype a lo-fi Ubi. Comp app – Independent judges rate the quality of designs – Identify “shared language” used – Questionnaire on usefulness of patterns 10
Design Patterns Ubi. Comp Patterns Evaluations Take-Away Ideas • Goal: identify design patterns for Ubi. Comp in order to help designers form higher-quality designs faster and to develop a “shared language” • Design patterns for Ubi. Comp are categorized at varying levels of abstraction underneath a set of main themes • Design patterns should be evaluated rigorously • The community is welcome to submit patterns to http: //kettle. cs. berkeley. edu/ubicomp 11
Thanks! Any questions or comments? http: //kettle. cs. berkeley. edu/ubicomp 12
Design Patterns Ubi. Comp Patterns Evaluations What does a pattern look like? • Design patterns typically range from 3 -5 pages and provide general but descriptive methods for solving a particular problem • A sensitizing image is useful for easy identification of the pattern • Problems encountered may never be solved in an exact way and therefore design patterns are never too specific • A Background suggests how the pattern is useful and how it can be combined with other patterns • The Problem statement identifies a recurring problem in the discipline • The Solution statement identifies the common solutions and provides details, suggestions, and tradeoffs 13
Design Patterns Ubi. Comp Patterns Evaluations Patterns in other Disciplines • In the mid-1990 s, patterns became popularized in other disciplines such as Software Engineering, Web Site Design, and UI Design. – Design of Sites, Douglas K. van Duyne, James A. Landay, Jason I. Hong – Design Patterns, Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides 14
Design Patterns Ubi. Comp Patterns Evaluations Ubi. Comp Genres • Most Ubi. Comp applications can be classified under the following application genres: – – – Business (i. e. Parc. Tab) Care and Maintenance (i. e. Context-Aware Clinics) Collaboration (i. e. Blue. Board) Education (i. e. Classroom 2000) Emergency Response (i. e. Siren) Fieldwork (i. e. Field. Note) Guides (i. e. Cyber. Guide) Laboratory (i. e. Plant. Care) Memory Aids (i. e. Personal Audio Loop) Smart Homes (i. e. Georgia Tech’s Aware Home) Smart Vehicles (i. e. Context-Aware GM) 15
- Slides: 15