Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus
Published at
IEEE Transactions on Visualization and Computer Graphics
2017
Abstract
The growing volume and variety of data presents both opportunities and
challenges for visual analytics. Addressing these challenges is needed for big
data to provide valuable insights and novel solutions for business, security,
social media, and healthcare. In the case of temporal event sequence analytics
it is the number of events in the data and variety of temporal sequence patterns
that challenges users of visual analytic tools. This paper describes 15
strategies for sharpening analytic focus that analysts can use to reduce the
data volume and pattern variety. Four groups of strategies are proposed: (1)
extraction strategies, (2) temporal folding, (3) pattern simplification
strategies, and (4) iterative strategies. For each strategy, we provide examples
of the use and impact of this strategy on volume and/or variety. Examples are
selected from 20 case studies gathered from either our own work, the literature,
or based on email interviews with individuals who conducted the analyses and
developers who observed analysts using the tools. Finally, we discuss how these
strategies might be combined and report on the feedback from 10 senior event
sequence analysts.