Now showing items 1-10 of 10

  • Changing the view: towards the theory of visualisation comprehension 

    Shovman, Mark; Szymkowiak, Andrea; Bown, James L.; Scott-Brown, Kenneth C. (Institute of Electrical and Electronics Engineers, 2009-07)
    The core problem of the evaluation of information visualisation is that the end product of visualisation - the comprehension of the information from the data - is difficult to measure objectively. This paper outlines a ...
  • Engineering simulations for cancer systems biology 

    Bown, James L.; Andrews, Paul S.; Deeni, Yusuf Y.; Goltsov, Alexey; Idowu, Michael A.; Polac, Fiona A.C.; Sampson, Adam T.; Shovman, Mark; Stepney, Susan (Bentham Science Publishers, 2012-11)
    Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico ...
  • Information visualization and the arts-science-social science interface 

    Bown, James L.; Fee, Kenneth; Sampson, Adam T.; Shovman, Mark; Falconer, Ruth E.; Goltsov, Alexey; Issacs, John P.; Robertson, Paul; Scott-Brown, Kenneth C.; Szymkowiak, Andrea (ACM, 2010)
    In a world of ever-increasing and newly discovered complexities, and rapidly expanding data sets describing man-made and natural phenomena, information visualization offers a means of structuring and enabling interpretation ...
  • Is visual search a high-level phenomenon? Evidence from structure perception in 3-D scatterplots 

    Shovman, Mark; Szymkowiak, Andrea; Bown, James L.; Scott-Brown, Kenneth C. (Pion, 2010)
    Increasing use of 3-D scatterplots for trend detection in visual analytics, raises the theoretical question: what constitutes an object in such a task? Previously (Shovman et al, 2008 Perception 37 79 ^ 80) we have shown ...
  • The meaning of graphs: scatterplots as a test-bed for theories of object-hood 

    Shovman, Mark; Scott-Brown, Kenneth C.; Szymkowiak, Andrea; Bown, James L. (Wolfgang Krammer, 2012)
    The burgeoning field of visual analytics offers a novel area for research in principles of Gestalt, specifically in the definitions of object-hood. Abstract visualisations are parsed into perceptual objects that are rich ...
  • Measuring comprehension of abstract data visualisations 

    Shovman, Mark (Abertay University School of Social and Health Sciences, 2011-10)
    Common visualisation techniques such as bar-charts and scatter-plots are not sufficient for visual analysis of large sets of complex multidimensional data. Technological advancements have led to a proliferation of novel ...
  • A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery: SiViT 

    Bown, James L.; Shovman, Mark; Robertson, Paul; Boiko, Andrei; Goltsov, Alexey; Mullen, Peter; Harrison, David J. (Impact Journals, 2016-05-18)
    Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the ...
  • Twist and learn: interface learning in 3DOF exploration of 3D scatterplots 

    Shovman, Mark; Bown, James L.; Szymkowiak, Andrea; Scott-Brown, Kenneth C. (ACM, 2015)
    The increasing availability of 3D interfaces brings promise of improved user experience in diverse areas. Our study focuses on visual analytics, testing whether 3D interactivity improves performance in a visual data ...
  • Use of 'pop-out' paradigm to test graph comprehension in a three-dimensional scatter plot 

    Shovman, Mark; Scott-Brown, Kenneth C.; Szymkowiak, Andrea; Bown, James L. (Pion, 2008)
    The emerging field of visual analytics applies abstract data visualisations to analyse complex, multivariate data. Data visualisations comprise a full spectrum of pictorial and symbolic elements; thus, juxtaposing theories ...
  • Visualizing complex systems 

    Falconer, Ruth E.; Shovman, Mark (PerAda (Pervasive Adaptation), 2010-09-30)