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J. Haider, M. Pohl, C. Pallaris, W. Wong:
"Supporting Sense-Making and Insight Processes in Visual Analytics by Deriving Guidelines from Empirical Results";
Talk: International Summer School on Visual Computing 2015, Rostock, Germany; 2015-08-17 - 2015-08-21; in: "Proceedings of the Internation Summer School on Visual Computing 2015", (2015), ISBN: 978-3-8396-0960-6; 59 - 68.

We need analytics systems that are optimised to human
sense-making and reasoning due to the amount of data that is available
for intelligence analysis. The purpose of Visual Analytics is to enable
and discover insights in complex data through automatic computation
and interactive visualisation. Sense-making describes the process of giv-
ing meaning to one's experience in order to understand events. To do so
interactivity is the essential key to make sense out of data because the
limits of human capacities are reached quickly. It is, however, not su -
ciently clear how analysts derive knowledge from information systems. In
this work, we investigate interaction processes with visual analytics tools
to improve the understanding on how this meaning is generated. Addi-
tionally, guidelines based on empirical research and user requirements
are presented.

insight model, decision making, design recommendations