Visualisation Tools

There are hundreds of visualisation tools and packages used by researchers at University of Oxford and beyond. The IDN cannot hope to be a reference or a recommendation engine for all of these solutions. For a birds eye view of what tools are available you might find this resource useful: http://www.visualisingdata.com/resources/.

In general, visualisation tools fall into one of two categories:

  • Point and Click Tools: These allow users to build visualisations interactively, for instance selecting columns from a spreadsheet-like view of your data and clicking “Create BarChart”. Examples of this type of tool include: Excel, SPSS and Tableau.
  • Scripting Tools: These require users to write code (or scripts) to generate visualisations, such tools in general have a steeper initial learning curve than “point and click tools” but allow greater overall flexibility and extensibility. Examples of this type of tool include: Python, R.

IDN Supported Tools

The IDN offers advice, support and consultancy in building interactive data visualisations that meet the following conditions:

  • Visualisations are hosted online.
  • Visualisation may be embedded in personal, research group or publisher websites (via <iframe></iframe>)
  • The data behind the visualisations is made available for download and subject to an appropriate data license.

Additionally, the IDN provides Shiny app hosting for University of Oxford researchers - which you may read about on the IDN Shiny Apps page.

Plotly

Plot.ly is a website that allows users to create interactive data visualisations in the web browser with a very easy to use point and click interface. With a free account it is only possible to create public visualisations with the underlying data also made publically available.

The actual visualisation magic behind the plot.ly website comes from the underlying JavaScript library, plotly. There is a high-level binding to the plotly library available in both R and python, which is described in detail here. You’ll find many examples of visualisations built using the plotly htmlwidget library using R in this website, particularly in the charts section

R

We have a page dedicated to R

Shiny

Great

Tableau

We have a page dedicated to Tableau