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  • How was the data prepared and combined for visualization (by filtering, transforming, calculating and enriching)?
  • What purpose does the visualization serve?
  • Why has this type of visualization been selected?
  • How have the colours, sizes and shapes in the visualization been determined?
  • What software has been used and why? What computational methods does the research employ?
  • Which settings and algorithms were applied?
  • How have the decisions related to the above-mentioned questions highlighted or downplayed aspects of the underlying data set?

Visualization tools

  1. SHANTI Interactive Visualization Analytics  An HTML5-based web application that makes it easy to create elements such as data, charts, maps, images, timelines and video
  2. Palladio  A browser-based free tool to visualize historical data (trends, maps, networks)
  3. RAW Graphs  A browser based free tool to visualize various types of numerical or categorical data, with a large selection of chart types
  4. Google Charts and Google DataStudio  Powerful tools to visualize data from Google sheets
  5. Orange  Tool for visualizing data in, e.g., heat maps
  6. Gephi  Leading visualization and exploration software for network data. Gephi is open-source and free.
  7. VOSviewer  For constructing and visuaizing bibliometric networks.

NB! Many of these tools are offered for free and developed by academics with no compensation. When using these tools, make sure you add a reference to the tool if instructed (e.g., Gephi).

Small selection of materials to illustrate the possibilities of visualization:

The Data Visualizartion Catalogue has en extensive gallery of different chart types and their uses.


Tufte, Edward (1983/2001). Visual display of quantitative information. Cheshire, CT: Graphics press. (Helka)

Critical literature on data visualization

Kennedy, H. & Engebretsen, M. (2020) (Eds.). Data Visualization in Society. Amsterdam University Press.