Projects

magic-table

A Magic Table By Dr Greg Ross See more of your data at a glanceThe Magic Table is a JavaScript library that allows you to see more in your data by applying some simple visual techniques to transform a table. Information VisualisationThe examples show how you can obtain a barchart or ... [More] scatterplot view in the table as well as a novel approach to displaying a lot more of your data without using up much valuable screen real estate. The latter technique has adopted the concept of spatial distortion, using a fisheye lens model. Reducing the row height and column widths so that all of the cells become visible and using colour to encode the cell values affords the user an informative overview of all the data in one go. By moving a lens over this overview we can magnify the cells under the lens so that we obtain detail within the overview. Google visualisation APIThe library has now also been wrapped in Google's visualisation API. Here's an example of how to use it this way. Easy to useDownload or checkout the code and follow the walk-through or the example web pages to quickly create a magic table. BrowsersThe library has been tested in Firefox, Opera, Safari and Chrome. It's super-fast in Safari. However, since it uses the canvas element, it does not work in Interner Explorer (boooooooooooooo!). I tried to get it to work with ExplorerCanvas but IE is stupendously slow when it comes to VML path rendering. In fact, Internet Snorer is around 10 orders of magnitude slower than Safari! Alas, I decided not to continue my effort in making it compatible with IE. Instead, it is intended that the library is used in applications that have, wisely, embedded a non-IE browser engine such as Gecko or Presto. Click on the images below to see working examples: [Less]

cgvis

CGVis is a generic data visualization tool with an innovative zoomable user interface and animations which helps users to explore multidimensional data and find particular features in it. CGVis was greatly inspired by HCE (Hierarchical Clustering Explorer) of the University of Maryland. It was ... [More] conceptually designed at the Graz University of Applied Sciences FH JOANNEUM by Jochen Martin, Karl Lampret and Ilya Boyandin and was then developed by Ilya Boyandin and Erik Körner. CGVis runs on any Java SE-enabled platform. Features: Zoomable heat map view providing an overview of the whole input dataset Hierarchical clustering of elements and attributes Dendrogram in the heat map view Zoomable scatter plot view (2, 3, or 4 selected attributes are visualized by the dots' positions, sizes, and colors) Smooth animation in the scatter plot view when changing the axe/size/color attributes Element selection synchronization between the views Support for CSV input files Support for the XML-based CGV file format that provides facilities to load the input data from a database (see CGVis DataSources for details) Input data normalization (enabled by default) More screenshots Requirements: Java Standard Edition 5.0+ (can be freely downloaded here) Watch this demo for a quick overview (you can also download the demo as a zip archive here). If you have any questions or suggestions about CGVis, feel free to contact me via email: ilyabo@gmail.com. [Less]

gridsphere-visualization

visualization for gridsphere