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Copyright © 2005, Pearson Education, Inc. Slides from resources for: Designing the User Interface 4th Edition by Ben Shneiderman & Catherine Plaisant Slides developed by Roger J. Chapman
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Copyright © 2005, Pearson Education, Inc. Introduction Information overload and anxiety common Developing more powerful search and visualization methods, integration of technology with task Terms: –Information gathering –Seeking –Filtering –Visualization Huge volumes of available data: –Data mining –Data warehouses and data marts –Knowledge networks or semantic webs –A know-item-search versus making sense and discovering
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Copyright © 2005, Pearson Education, Inc. Introduction Traditional interfaces have been difficult for novice users –Complex commands –Boolean operators –Unwieldy concepts Traditional interfaces have been inadequate for expert users –Difficulty in repeating searches across multiple databases –Weak methods for discovering where to narrow broad searches –Poor integration with other tools Designers are just learning how to present large amounts of data in orderly and user-controlled ways
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Copyright © 2005, Pearson Education, Inc. Information visualization "A picture is worth a thousand words!" Large amounts of information in compact and user- controlled ways –example: USA map, click a city to see more info Information visualization can be defined as the use of interactive visual representations of abstract data to amplify cognition Scientific visualization –continuous variables, volumes and surfaces Information visualization –categorical variables and the discovery of patterns, trends, clusters, outliers, and gaps
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Copyright © 2005, Pearson Education, Inc. Information visualization Visual data mining Answer questions users didn’t know they had Tufte offers advice for static information, but dynamic displays present a challenge Must be more than cool The Visual Information Seeking Mantra –Overview first –zoom and filter –then details-on-demand
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Copyright © 2005, Pearson Education, Inc.
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Examples TextArc SeeSoft Piccolo Copyright © 2005, Pearson Education, Inc.
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Information visualization Basic data types –1 - Dimensional Linear data types include textual documents, program source code, lists of names in sequential order E.g. highlight lines of code that have changed –2 - Dimensional Planar or map data includes geographic maps, floor plans, newspaper layouts E.g. Geographic Information Systems, spatial displays of document collections Example tasks: find regions containing items
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Copyright © 2005, Pearson Education, Inc. Information visualization Basic data types (cont.) –3 - Dimensional Real-world objects such as molecules, the human body, buildings Users must cope with understanding their position and orientation when viewing the objects E.g. overviews, landmarks, stereo displays, transparency, color coding Virtual Reality displays Users’ tasks typically deal with continuous variables National Library of Medicine's Visible Human Project Controversial
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Copyright © 2005, Pearson Education, Inc. Information visualization Basic data types (cont.) –Multi-Dimensional Most relational and statistical databases N attributes become points in an n-dimensional space Interface representation could be a 2-D scattergram with each additional dimension controlled by a slider Parallel coordinate plots Table Lens Hierarchal or k-means clustering
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Copyright © 2005, Pearson Education, Inc. Information visualization Basic data types (cont.) –Temporal Time Lines are widely used and accepted Items have a start and finish time and items may overlap Tasks include finding all events before, after, or during some time period –Tree Collections of items with each item having a link to one parent item (except root) Outline style of indented labels or node-and-link diagram Space-filling approach –Networks Sometimes data needs to be linked to an arbitrary number of other items Example: A graphical representation of the World Wide Web Mode-and-link diagrams, matrices
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Copyright © 2005, Pearson Education, Inc. Information visualization Basic tasks –Overview Gain an overview of the entire collection Adjoining detail view The overview might contain a movable field-of-view box to control the contents of the detail view –allowing zoom factors of 3 to 30 Fisheye view –Zoom Zoom in on items of interest Allows a more detailed view Need to maintain context Particularly important for small displays –Filter Filter out uninteresting items Allows user to reduce size of search
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Copyright © 2005, Pearson Education, Inc. Information visualization Basic tasks (cont.) –Details-on-Demand Select an item or group and get details when needed Useful to pinpoint a good item Usually click on an item and review details in a separate or pop-up window –Relate View relationships among items Use human perceptual ability – proximity, containment, connected line, color coding Example: Set directors name, and view all movies with that director –History Keep a history to allow undo, replay, and progressive refinement Allows a mistake to be undone, or a series of steps to be replayed –Extract Extract the items or data Save to file, print, or drag to another application
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