Arrowad Visualization Approach
based a taxonomy proposed by Robert Amar, James Eagan, and John Stasko from GIT, USA

Determine Range
Given a set of data cases and an attribute of interest, find the span of values within the set.
Characterize Distribution
Given a set of data cases and a quantitative attribute of interest, characterize the distribution of that attribute's values over the set.
Find Anomalies
Identify any anomalies within a given set of data cases with respect to a given relationship or expectation.
Cluster
Given a set of data cases, find clusters of similar attribute values.
Correlate
Given a set of data cases and two attributes, determine useful relationships between the values of those attributes.
Retrieve Value
Given a set of specific cases, find attributes of those cases.
Filter
Given some concrete conditions on attribute values, find data cases satisfying those conditions.
Compute Derived Value
Given a set of data cases, compute an aggregate numeric representation of those data cases.
Find Extremum
Find data cases possessing an extreme value of an attribute over its range within the data set.
Sort
Given a set of data cases, rank them according to some ordinal metric.