Improving Proactive Decision Making with Object Trend Displays

Abstract

Operators of dynamic systems often use time-series data to support their diagnostic and proactive decision-making. Those data have traditionally been displayed in the form of separate trend charts, for example, line graphs of pressure and temperature over time. Configural object displays are a widely advocated approach to the visual integration of information yet have been applied only rarely to time-series data. One example was the 'time tunnel' format but its benefits were equivocal, seemingly compromised by its graphical complexity. There is then the need to investigate other graphical forms for object displays of time series data.

This research will require a microworld representing a knowledge-rich task domain accessible to multiple participants (the nuclear power plant simulation used with the time tunnel display studies required participants to have 20 hours of experience with the system). We report a design for such a microworld that adopts the domain of financial control of a business where decisions need to be made about the pricing of products to optimize returns in a changing and sometimes volatile market. Alternative visual displays of the essential time series data for this domain are possible and whilst decision making is knowledge rich, involving reasoning about high level relationships, pilot tests showed that it is accessible to participants with only moderate training.

Title: Improving Proactive Decision Making with Object Trend Displays

Authors: Alex Eftychiou and John Dowell

Publication: Proceedings of ECCE '16: the European Conference on Cognitive Ergonomics, Article No. 19 | full text (PDF)

Year: 2016

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