Transcript info-viz
Slides from resources for: Designing the User Interface 4th Edition by Ben Shneiderman & Catherine Plaisant Slides developed by Roger J. Chapman 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 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 Copyright © 2005, Pearson Education, Inc. Information visualization • "A picture is worth a thousand words!" • Large amounts of information in compact and usercontrolled 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 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 Copyright © 2005, Pearson Education, Inc. Copyright © 2005, Pearson Education, Inc. Examples • TextArc • SeeSoft • Piccolo Copyright © 2005, Pearson Education, Inc. 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 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 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 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 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 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 Copyright © 2005, Pearson Education, Inc.