Visual Analytics

  • Ian T. NabneyEmail author
Part of the Emergence, Complexity and Computation book series (ECC, volume 35)


We are in a data-driven era. Making sense of data is becoming increasingly important, and this is driving the need for systems that enable people to analyze and understand data. Visual analytics presents users with a visual representation of their data so that they make sense of it: reason about it, ask important questions, and interpret the answers to those questions. This paper shows how effective visual analytics systems combine information visualisation (to visually represent data) with machine learning (to project data to a low-dimensional space). The methods are illustrated with two real-world case studies in drug discovery and condition monitoring of helicopter airframes. This paper is not the final word on the subject, but it also points the way to future research directions.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of EngineeringUniversity of BristolClifton, BristolUK

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