1. 14. Information Search and Visualization

2. Introduction
information retrieval, database management  information gathering, seeking, filtering, or visualization
data mining from data warehouses and data marts  knowledge networks or semantic webs
information search using traditional UI – hurdle for novice users and an inadequate for experts
Improvements on traditional text and multimedia searching seem possible as a new generation of visualization strategies for query formulation and information presentation emerges
task actions (browsing or searching) represented by interface actions (scrolling, zooming, joining, or linking)
Tasks – specific/extended fact finding, exploration of availability, open-ended browsing and problem analysis

3. Searching in Textual Documents and Database Querying
search engine
SQL – requires training, and even then users make frequent errors
natural-language queries – appealing but limited computer processing capacity
form-fillin queries and query-by-example
simple and advanced search interfaces (fig. 14.1)
five-phase framework
Formulation: expressing the search  source, fields, phrases, variants
Initiation of action: launching the search  explicit, implicit initiation, dynamic query
Review of results: reading messages and outcomes  sequence and cluster
Refinement: formulating the next step  history buffer
Use: compiling or disseminating insight

4. Multimedia Document Searches
Image search -- query by image content (QBIC)  search for distinctive features or search for distinctive colors
Map search – search by features
Design or diagram search – finding engine designs with pistons smaller than 6 cm
Sound search – Music-information retrieval system
Video search
Animation search

5. Advanced Filtering and Search Interfaces
filtering with complex Boolean queries - difficulty of use
automatic filtering - user constructed set of keywords to dynamically generated information
dynamic queries - direct manipulation queries
faceted metadata search - integrating category browsing with keyword searching
collaborative filtering - each user rates items, and then system suggest unread items
multilingual searches
visual searches -

6. Information Visualization
How to present and manipulate large amounts of information in compact and user-controlled ways
Information visualization - the use of interactive visual representations of abstract data to amplify cognition
Resistance to visual approach - textual tools use compact presentations that are rich with meaningful information and comfortingly familiar
visual-information-seeking mantra – overview first, zoom and filter, then details on demand
Data type by task taxonomy (TTT) and seven tasks (Box 14.2)

7. Information Visualization
1-D 1inear data
in a sequential manner – textual documents, dictionaries, alphabetical list of names
interface-design issues include what fonts, color, size to use, and what overview, scrolling, or selection methods to provide for users
2-D map data
maps, floor plans, newspaper layouts
interface-domain features (size, color, opacity)
user tasks – to find adjacent items, regions containing items, paths between items and to perform the seven basic tasks

8. Information Visualization
3-D world data
Computer-assisted medical imaging, architectural drawing, mechanical design, chemical structure modeling, and scientific simulations
users’ tasks typically deal with continuous variables such as temperature or density
cope with the position and orientation when viewing the objects  potential problems of occlusion and navigation  overviews, landmarks, teleoperation, multiple views and TUI
Multidimensional data
n attributes in a n-dimensional space
tasks include finding patterns such as, clusters, correlations, gaps and outliers
three-dimensional scattergram (disorientation and occlusion)

9. Information Visualization
Temporal data
items have a start and finish time, and that items may overlap
finding all events before, after, or during time period and the seven basic tasks
Tree data
Treemap
Network data
shortest or least costly paths connecting two items or traversing the entire network

10. Information Visualization
Overview task
zoom-out views of each data type to see the entire collection plus detail view
movable field-of-view box (zoom factors of 3 to 30), fisheye strategy
Zoom task
to control zoom focus and zoom factor
Filter task
sliders, buttons, or other control widgets coupled with rapid display update

11. Information Visualization
Details-on-demand task
simply click on an item to get a pop-up window with values of each of the attributes
Relate task
proximity, containment, connection, color coding; highlighting
History task
history of actions to support undo, replay, and progressive refinement
Extract task
extract , save, send by electronic mail, insert, publish

12. Information Visualization
Challenges for information visualization
import data
combine visual representations with textual labels
see related information
view large volumes of data
integrate data mining
collaborate with others
achieve universal usability