Data visualisation

Following our intent of providing the reader a complete guidebook to physiological data processing, we already talked about where to find data, or how to collect it, how to analyse it and which tools to use, and even how to face possible negative results. However, one of the important steps we didn’t yet cover is data visualisation. Either if you want to inspect your data as a previous stage of analysis, or if you want to represent your results, data visualisation is a key step to perform while processing data.

©neuroelectrics8

©neuroelectrics

Traditional processing frameworks already provide toolsets for data visualisation. Matlab, for example, comes with its own data plotting and graphic drawing tools. Their plots are so commonly used among scientific community that its plotting style and looks are easily distinguishable. Other common data processing frameworks, like Octave or Mathematica also come with their own integrated data visualisation tools.

But what can you do if your processing software’s integrated tools don’t suit your needs? Or if, plainly, you don’t work with any framework that has data visualisation integrated. Then you’ll need to use third party data visualisation libraries or softwares. One interesting software to use for data visualisation is Tableau. One important feature of Tableau is that community can contribute with new layout and visualisation designs.

Not being standalone software pieces, but rather programming libraries, there are a lot of possibilities. Among the commonly used ones are Gnuplot, PLplot, matplotlib, Chaco. All those libraries are designed to be used with programming languages and using the user screen as a primar display. Therefore, in order to export the output to other displays, like printing-ready formats or online formats, further steps need to be performed.

An important trend in data visualisation is to display the visualisation in online documents or, even, stream formats. Libraries to display data visualisation in mediums like webpages, online canvas and similar formats are becoming very popular. One of the most popular of such libraries is D3. With dozens of available layouts and designs, it offers a very powerful tool for data visualisation that will be displayed on any javascript rendering device (like desktop browsers, mobile devices, smart TVs, etc.). Similar to D3, javascript libraries are Flot, Vega, Raw and Dygraph.

Do you know of other interesting data visualisation libraries or software? Please contribute to the grow of this post by letting us know, and we’ll gladly add your inputs!

 

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