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The role of visualization is to make the data more understandable for the human interpreter and to give a bird's eye view of the data. Visualization makes it easier to detect different kinds of patterns, anomalies and trends in the data regardless of the size of the data. Furthermore, visualization makes it easier to communicate the results of the research and locates the meaning of complex data sets. There are various ways to visualize digital data, and the correct means of visualization depends on the purpose of it and of the data used. 

Visualizations are often a good way to summarize your results and very useful in presentations.

Remember, however, that visualizations are often products of several choices made by the researcher or the software and various functions used in the software. Therefore they should be always interpreted carefully and critically, and results should rarely be based on interpreting visualizations only.

The following questions could be valuable when interpreting visualizations (van Es et al. 2017):

  • 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.

The Data Visualization page of the DMI Masters of Media Wiki includes general information, theory, examples and tools related to data visualization.

Eder, Maciej (2020). Visualization in Stylometry: Cluster Analysis Using Networks. Digital Scholarship in the Humanities 32:1, 50-64.

Europe Elects

  • A German-based start up that focuses on the analysis of polls and election data in Europe
  • Their site and social media includes a vast number of charts and other visualizations about European elections.

Databyro (Fin)

  • Election data and visualizations of Finnish politics

Grandjean, Martin (2016). A Social Network Analysis of Twitter: Mapping the Digital Humanities Community. Cogent Arts and Humanities 3:11, 1-14.

Smith, Marc et al. Analyzing (Social Media) Networks with NodeXL. C&T'09,  255-263.

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. 

MacKenzie, A., & McNally, R. (2013). Living Multiples: How Large-scale Scientific Data-mining Pursues Identity and Differences. Theory, Culture & Society 30:4, 72–91.

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