Information Visualization
Information & Visualization
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Information visualizations are metrics expressed as graphics.
Information visualizations are metrics expressed as graphics with labels.
What graphic? (Adopted from the now-defunct Many Eyes site) Relations among data points Scatterplot Matrix chart Parts of a whole Pie chart Tree map Change over time Line graph Stack graph Compare values Bar chart Bubble chart Analyze text Word tree Tag cloud Phrase net Relations Networks Flow charts Organizational charts
Pie Chart Tree Map
different-x-val
Column Chart Bar Chart Large # of data sets10-12 max Long labelsShort labels Beware of proportions, broken columns, and start values!
Negative Values
It shows the number of burglaries versus the number of murders per 100,000 population. Every bubble is a state of America, the size of the bubbles represents the population of the state and the color is the number of larcenies. (check this site if you want some python scripts for converting data to visualizations) (check this site for animated visualizations)
(play with these visualizations)
Network principles: 1)Degree centrality: # of direct relationships (numerical) 2)Betweenness centrality: ability to make connections to others (positional) 3)Closeness: speed of access (relative) 4)Eigenvalue: closeness to other close entities (comparative) 5)Authority (many entities point to it) Display: force-directed (optimizes display with least number of crossings; edges more or less the same length; spring-loaded repulsion; attraction constrains layout).
Beware of reading the incidental information of the graphic as if it were the data and/or phenomenon from which the data was extracted.
Minard, 1849, Ports in Europe and tonnages
NION.html NION.html nytimescom/ nytimescom/ projects-of-2011/ projects-of-2011/
958.ibm.com/software/analytics/manyeyes/ ibm.com/software/analytics/manyeyes/