The Future of Computing (Now and Then) – Visualisation


Visualisation, as the name implies, is about methods or techniques of displaying (visualising) data, in such a manner that the result is further and better understanding of the underlying information or knowledge of the data, what the data is “imparting” to the audience.

Visualisation is closely aligned with Analytics in many ways, in that Visualisation is all about how to present large volume and complex data in such a manner that it is (relatively) simple for humans to understand the underlying message, or pattern, represented or conveyed by the data. Typically, the analytics process will apply algorithms to process the data in a variety of manners, hopefully obtaining a suitable result – which then needs to be presented such that decisions can be made and further action can be taken. In many instances, the analytic process itself may involve Visualisation in order to allow the people performing the analytics to determine what to do next.

These insights into the data – what it is trying to tell us – are imparted through the power of the human mind, through its ability to make connections and understandings according to visual cues (and prior knowledge). Interestingly, the ability for humans to understand based on visualisation is mainly achieved through additional computing processing – advanced visualisation typically involves advanced information processing (and sometimes advanced hardware for particular visualisation purposes, such as 3D displays, large screen projections, etc). It should be noted though, that visualisation has been around for quite some time – early maps are a form of visualisation – producing a visual representation of some data to assist in understanding (see http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf).

In the past, Visualiation has been part of Business Intelligence (think charts, graphs, dashboards), but in a rather simple and simplistic manner. Modern visualisation uses all the power of graphics and animation (including 3D) to present a compelling vision for decision making. Visualisation today is much much more than a few charts and graphs. It is many different types of graphical representations; it is animated timelines (combined with multiple graphic types); it is now 3D (both static and animated) and it is interactive (the initial visualisation can allow those viewing to select an element, which will then query for new data (for instance, more detailed information which is then visualised (possibly using a different mode of visualisation) and allows for further interaction).

Some disciplines and specialist areas only operate based on visualisation. Areas include:

Computed Axial Tomography (CAT) and Magnetic Resonance Imaging (MRI) scans in medicine only “work” because the massive amounts of data generated are presented in a visual form for the specialist physician to interpret. The physician never works with the raw data – only with a computed representation (http://www.humansfuture.org/visualize_scientific_visualization.htm). Astronomers now regularly use visualisation to process the huge amounts of data generated by modern telescopes (current estimates suggest that this data stream will exceed 1 Terabyte of data per day in the near future – see http://astronomy.swin.edu.au/scivis/ and http://astrocompute.wordpress.com/2011/03/04/scientific-visualization-in-astronomy-towards-the-petascale-astronomy-era/) to visualise and understand how the universe works – and what it looks like, from a variety of perspectives – not simply in the human visual spectrum, but also in the infrared and ultraviolet wavelengths, as well as gamma radiation and other signals. Geospatial data, such as topography, hydrography, etc, are all presented in terms of visualisation – as simple as a mapping display, up to as complicated as real-time 3D animation through a timeline.

Visualisation today is enabled by hardware advances, specifically the inclusion of Graphical Processing Units (GPUs) in computers (specifically PC based hardware) – offloading the processing for visualisation from the standard CPU onto a dedicated and high-powered chip (see http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F9449%2F29999%2F01372245.pdf%3Farnumber%3D1372245&authDecision=-203; http://astrocompute.wordpress.com/2011/04/15/gpus-vs-cpus-apples-vs-oranges/ and http://astronomy.swin.edu.au/scivis/).

An excellent visualisation graphic of the different types of visualisations which can be produced, categorised into six different types (data; information; concept; strategy; metaphor and compound) has been produced by Visual Literacy (which provides e-Learning tutorials on visualisation – see http://www.visual-literacy.org/) and is available at http://www.visual-literacy.org/periodic_table/periodic_table.html. The web page is interactive, displaying an example of each type of visualisation when mousing over the entry box in the table. An excellent example of how to do visualisation well!

Some of the specific techniques used for visualisation include:

  1. a Cladogram (for display of phylogeny – see http://darwiniana.org/trees.htm; http://www.scribd.com/doc/51895193/6/Cladograms-and-Trees; http://cnx.org/content/m11052/latest/; http://www.crescentbloom.com/ii/l/17.htm; http://www.dinosauria.com/jdp/misc/cladogram.html);
  2. a Dendrogram (for display of classifications – see http://botanydictionary.org/dendrogram.html; http://www.nonlinear.com/support/progenesis/samespots/faq/dendrogram.aspx; http://www.mathworks.com/help/toolbox/stats/dendrogram.html);
  3. Graph drawing (http://graphdrawing.org/; http://gdea.informatik.uni-koeln.de/; http://www.ogdf.net/doku.php);
  4. Heat-maps (http://www.cs.uic.edu/~wilkinson/Publications/heatmap.pdf; http://www.patrick-wied.at/static/heatmapjs/; http://ashleylab.stanford.edu/tools_scripts.html; http://www.bioinformatics.ubc.ca/matrix2png/);
  5. Hyper Trees (http://www.sigchi.org/chi95/Electronic/documnts/papers/jl_bdy.htm; http://hypergraph.sourceforge.net/; http://thejit.org/; http://ucjeps.berkeley.edu/map2.html; http://www.touchgraph.com/navigator);
  6. Treemapping (http://www.magnaview.nl/documents/Visualizing_Business_Data_with_Generalized_Treemaps.pdf; http://www.perceptualedge.com/articles/b-eye/treemaps.pdf; http://www.cs.umd.edu/hcil/treemap-history/index.shtml; http://iv.slis.indiana.edu/sw/treemap.html).

In the future, such visualisation will link to differing models of Human Computer Interaction (HCI), including various forms of haptics (“The science of applying tactile sensation to human interaction with computers” – source: http://foldoc.org/haptics. Also see: http://www.immersion.com/docs/Value-of-Haptics_Jun10-v2.pdf) and immersive technologies, such as the multi-touch desktop (see http://www.perceptivepixel.com/ – similar to the technology hypothesized in the movie The Minority Report, based on the short story of the same name by Philip K. Dick).

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