W08 Data Visualisation Flashcards
Why visualize?
explorative analysis
- manual datamining
- find and see connections
decision support and management information
-quick overview of relevant trends and patterns
presentation and argumentation
- underline arguments with quantiative data
- ethics!
Good Visualization
- all relevant data (no more)
- think content, not presentation
- no distortion
- make large data understandable
- enable comparisons
- layer details from overview to finer points
- clear purpose
- integrated in context of representation
substance + data analysis+ design
3 steps for effective visualization
formulate question
gather and analyze data
apply visual representation
Distorting data
- y -axis scale
- modify base line
- switch aggregation level
- areas for one-dimensional data
- visual effects
Deception and ethics!!
Histogram - beware of?
bin size!
Detail - Distribution - detail deprivation
Pie Charts - beware of?
Proportions!
Images and Quantities
direct labels (axes) encoding (color and shadow) self-representation (known objects)
maximize information content
- smallest effective difference
- minimize ink
- avoid chart junk
Use of Color
Sequential -nice
diverging - ok
qualitative - meh
Use negative space
invert colors
Scaling of Graph
- axes min and max
- aspect ratio
- similarity to others
- beware of sacrificing comparabiltiy to understandbility
Show transformations?
multiples and parellelism
Infographics
tell a story through
- data visualization
- text
- images
Visual Story Telling
Introduction -why?
Main Event -what? aha
conclusion follow up?
Media Formats
static to interactive