Understanding Temporal Aspects of Digital Trace Data with Visual Analytics

Christian Tominski (), Wolfgang Aigner (), Silvia Miksch () and Heidrun Schumann ()
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Christian Tominski: University of Rostock
Wolfgang Aigner: St. Pölten University of Applied Sciences
Silvia Miksch: TU Wien
Heidrun Schumann: University of Rostock

Chapter Chapter 6 in Digital Trace Data Research in Information Systems, 2026, pp 107-146 from Springer

Abstract: Abstract Digital trace data are almost inevitably tied to the dimension of time simply because tracing only makes sense in relation to time. The dimension of time is therefore an essential aspect that deserves special attention in any attempt to understand digital trace data. This chapter focuses on understanding the temporal aspects of digital trace data using visual analytics. The premise of visual analytics is to combine visualization, interactivity, and data analysis methods into coherent tools that help people make sense of data. As a basis for developing of such tools, this chapter first specifies the characteristics of time and time-oriented data. Then, specific visualization, interaction, and data analysis techniques are introduced and illustrated with practical examples. The chapter concludes with an outline of challenges for future research in visual analytics in the context of time-oriented digital trace data.

Keywords: Visual analytics; Time; Data analysis (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-05497-5_6

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