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Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection

Rita Borgo Orcid Logo, Joel Dearden Orcid Logo, Mark Jones Orcid Logo

IEEE Transactions on Visualization and Computer Graphics, Volume: 20, Issue: 12, Pages: 2261 - 2270

Swansea University Authors: Rita Borgo Orcid Logo, Joel Dearden Orcid Logo, Mark Jones Orcid Logo

DOI (Published version): 10.1109/TVCG.2014.2346428

Abstract

In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts...

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Published in: IEEE Transactions on Visualization and Computer Graphics
Published: 2014
Online Access: http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf
URI: https://cronfa.swan.ac.uk/Record/cronfa18118
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Abstract: In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts, plots and colour on linear or logarithmic scales. These all suffer from related problems. There is a limit to the dynamic range available for plotting numbers, and so the required dynamic range of the plot can exceed that of the depiction method. When that occurs, resolving, comparing and relating values across the display becomes problematical or even impossible for the user. With this in mind, we present an empirical study in which we compare logarithmic, linear, scale-stack bars and our new markers for 11 different stimuli grouped into 4 different tasks across all 8 marker types.
College: Faculty of Science and Engineering
Issue: 12
Start Page: 2261
End Page: 2270