showing complex data
DESCRIPTION
Trees, Tables, and other information graphics. Showing Complex Data. Art of Information Graphics. Communicate visually rather than verbally Show rather than tell User’s can use their eyes and minds to draw their own conclusions - PowerPoint PPT PresentationTRANSCRIPT
Showing Complex DataTrees, Tables, and other information graphics
Art of Information Graphics
Communicate visually rather than verbally Show rather than tell User’s can use their eyes and minds to draw
their own conclusions When done well can be much more effective
than displaying verbal data, especially for complex data sets
Types of Information Graphics
Maps Flowcharts Bar Plots Graphs Diagrams Tables* TreeViews*
Power of Interactivity
We are dealing with computers not printed information
Use pop-ups, animation, etc to hide and show information to the user
Let the user modify, sort, etc – describe the data as they see fit to increase their ability to comprehend the data set.
Make the user a participant in the information discover process
Good Interactive Information Graphics Clearly shows how the data is organized Clearly shows what is related to what Clearly shows how to explore the data Clearly shows how the data can be rearranged Shows only what is needed to be known Allows the user to determine specific data
values
Data Organizational Models
Linear• List or single-variable plot
Tabular• Spreedsheet, multi-column list, sortable table, multi-y plot, etc
Hierarchical• Tree, cascaded lists, tree table, treemap, directed graph, etc
Network or Organic• Directed graph or flow chart
Graphical or Spatial• Map or schematic
Other• Parallel coordinate plots, treemaps, etc
Data Relationships
What’s Related to What Preattentive Variables?
Visual features that convey information before the view pays conscious attention to them
Gestalt principles of similarity and continuity are most often use to convey these relationships
Data RelationshipsPreattentive Variables
Data RelationshipsPreattentive Variables
Data RelationshipsPreattentive Variables
Data RelationshipsPreattentive Variables - Example
1.178739 0.699194 0.874042 0.291308 0.78357 0.745908 0.029079 0.521737
0.665048 0.776872 0.299437 0.585789 0.092586 1.055652 0.965067 0.021414
0.619581 0.393814 1.070211 0.306591 0.431111 0.176973 0.781644 1.042008
0.793146 1.077211 0.787416 0.384232 1.155947 1.104749 1.092146 0.81739
0.915559 1.01208 0.889061 0.509637 0.302029 0.872603 0.28545 0.59468
0.580484 1.150445 1.034182 0.062897 0.471185 0.544897 0.003143 1.011945
0.581041 0.265065 0.727255 0.31025 0.266997 0.741408 0.600416 1.040854
0.600723 0.552569 0.589978 0.198444 0.248 0.732601 0.69475 0.516055
1.112418 0.61739 0.291955 1.136749 0.379753 0.547165 0.004565 0.339588
0.399637 0.798155 1.044651 0.457568 0.281085 0.307115 0.457619 0.470444
0.242094 0.362186 0.627088 0.903784 0.622542 0.644447 0.503984 0.267117
0.101365 0.759558 0.386118 1.015149 0.381423 0.864015 0.956702 0.738639
0.271352 1.068867 0.217901 1.081866 0.328774 0.334843 0.545305 0.588397
0.803179 0.928343 0.503075 0.281974 0.284908 0.598675 0.544283 0.781571
0.203747 0.317019 0.222559 0.093807 0.913725 0.268272 0.899177 0.319825
0.068907 0.040848 0.057594 0.152116 0.965071 0.148314 0.857975 0.075507
0.905255 0.054391 0.542175 0.173376 0.192987 0.235287 0.443616 0.440908
0.035335 1.019702 0.848172 0.264228 0.91475 0.817566 0.052136 0.197727
0.016105 0.432765 0.592027 0.053195 0.849949 0.331346 0.968428 0.838117
1.065995 0.769864 0.90944 0.668404 0.768833 0.268052 0.398713 0.657809
0.457786 0.56645 1.032207 0.094762 1.082979 1.04981 0.814591 0.835953
0.750538 0.000213 0.461111 0.21911 0.112873 0.672291 0.051096 0.14064
0.712832 0.049231 0.104551 1.062568 0.506072 0.545243 0.703485 0.166171
0.787857 0.216091 1.029121 0.753735 0.757384 0.967038 0.241039 0.384356
0.341526 0.961132 1.021503 1.023409 0.624147 0.150229 0.106662 0.761185
1.050832 0.655706 1.071661 0.194237 1.083082 0.353512 1.028894 0.042028
0.260481 0.804218 0.794451 0.507621 0.591614 0.268941 0.408261 0.986109
Data RelationshipsPreattentive Color
Data RelationshipsAbility of preattentive color to scale
Data RelationshipsUse of multiple preattentive variables
Navigating and Exploring the Data Scroll and Pan
Drag or Scroll the viewable area until a point of interest is visible
Zoom Change the scale of the viewed section or point of
interest Open and close points of interest
Expand/Collapse to points of detail and interest Drill down into points of interest
Drilldown/drillup to points of detail and interest
Sorting and Arrangement of Data Choosing a good sort value, or letting the user
define it, can by a good method of arranging data in a useful manner
Common types of sort: Alpha, Numeric, Date, Time, Location, Category/Tag, Popularity, Custom, etc
Sorting and Arrangement of Data
SORTED BY LOCATION (ALPHA) SORTED BY VALUE
Searching and Filtering the Data Highly Interactive
Respond quickly to user’s searching and filtering Iterative
User refines search, query, filter until the result set is ideal
Contextual Shows results in context with surrounding data to
make it easier for a user to understand
Showing Specific Data Values
Labels Values shown directly in graphic Names on a Map, Values on a chart, etc
Legends Legends are used when color, texture, linestyle, symbol, etc, represent
the data values in the graphic Axes, Rulers, Scales, Timelines
Used when position represent values Datatips
Labels on mouse hover, tab, or other focus Data Brushing
Allows selecting a subset of data in the graphic to see how it fits or relates to data in other contexts
Common Patterns Power Tools
Overview Plus Detail Datatips Dynamic Queries Data Brushing Local Zooming
Tables and Lists Row Striping Sortable Table Jump to Item New-Item Row
Hierarchical Data Trees Cascading Lists Tree Table
Multidimensional Data Multi-Y Graph Small Multiples Treemap
Overview Plus Detail• Place an overview
graphic new to a zoomed “detail view”
• Best used when you want to user to see both the big picture and details of a portion of interest
• User here don’t need to see all details at once
• Zoomed region is typically movable in overview section
Data Tips As the mouse rolls over
points of interest, put the data values or additional information into a tooltip or floating window
Best used when you are showing an overview of the total data, but the graphic represents or has data behind what is shown
Data tips can be a quick and rewarding form of interactivity
Data Tips
Data Tips
Dynamic Queries Provide ways to
filter the data set immediately and interactively
Best used when data set is large and contains many variables and/or categories
Sliders and checkboxes often work well as controls to filter
Dynamic Queries
Dynamic Queries
Data Brushing Let the user select
data items in one view and show the same data selected in another view
Best used when you have two or more information graphics at a time.
Provides the ability to see a select group of points or items mapped against another metric or region
Data Brushing
Data Brushing
Data Brushinghttp://vitagate.itn.liu.se/projects/GAV/demovideos/VDE/VDE.html
Data Brushinghttp://vitagate.itn.liu.se/projects/GAV/demovideos/CoRelation/CoRelation.html
Local Zooming Show data in a single page.
Allow the mouse to select and area which in turn distorts the page and makes those data items large and readable
Best used when data set is some type of organizational form – plots, maps, networks, tables
Can include rearranging the data to show detail or fisheye zooming which enlarges a section without altering surrounding content
Local Zooming
Distorted Layout
Local Zooming
Fish Eye Zooming
Local Zooming
Row Striping Use two similar
shades to alternately color the backgrounds of table rows
Best used when a table’s row are difficult to separate visually
Often occurs when there are two many columns with various types or data or images
Colors should be low saturation and similar in hue
Row Striping
Row Striping
Clearly Better?
Sortable Table Show data in a
table and let the user sort the table rows according to column values
Best used when the interface contains many variable types the user may want to explore, group by, reorder, etc.
Jump to Item When user begins to type,
jump to that item in the list or table
Best used when the interface uses a scrolling list, table, drop down, combo box or tree to present a long set of items that are usually sorted by alpha
Keystrokes within a certain time interval (~200ms) are often honored to drive deeper into the name path
Jump to Item
Cascading Lists Express a hierarchy by
showing selectable lists of items at each level
Selection of an item shows that item’s children in subsequent list
Best used when your data is tree shaped but the hierarchy is deep and/or broad. A treeview would not work as well here due to the vast amount of scrolling that may be induced
Tree Table Put hierarchical data in columns, as you would a table; but use an indented
outline and controlling structure as would be seen in a tree Best used when you want to show hierarchical data represented by a tree,
but need to show more information than the item name itself. Can be used for sub-sorting in some cases
Tree Table
Tree Table+
Multi-Y Graph Stack multiple
graphs vertically and let them share the same X-axis
Y-axis for each graph represents a different metric
Best used when you want to show two or more graphs or data sets that share a common trait such as timeline
Multi-Y Graph
Small Multiples Create many small pictures of the data using two or three
dimensions Tile them on a page according to one or two additional data
dimensions Best used when you need to display a large data set with more than
two dimensions or over multiple variables over regular intervals
Small Multiples
Small Multiples
Small Multiples
Treemap Express multidimensional
and/or hierarchical data as rectangles of various sizes
The rectangles are nested to show hierarchy, color and/or labels show additional variables
Best used when data is tree shaped but each item has several attributes such as size and category that permit items to be grouped accordingly.
Users also want to see an overview of many data points.
Treemap
Tree Map
Treemap
Treemap
Deductive User Interface
Inductive User Interface
Good Inductive Interface answers What am I supposed to do now? Where do I go from here?
Inductive User Interface Focus each screen on a single task State the task Make the screen’s contents suit the task Offer links to secondary tasks Use consistent screen templates Provide screens for starting tasks Make it obvious how to carry out the task with controls
on the screen Provide an easy way to complete a task and start a new
one Make the next navigational step obvious
Case Study
Case Study – Focus?
Starting with a screen of tasks
2nd Tier Tasks
Accounts home page – Focus?
Design of secondary tasks
Screen Titles
Screen titles – State the task
Primary and secondary assistance