StatSilk founder Frank van Cappelle recently provided his insights on the benefits of data visualization, as part of an expert interview series at Podbox.

This article further elaborates on three key trends that are likely to shape the future of data visualization: automation, interactivity, and (VR) storytelling.


Not very long ago, data visualization was a difficult and tedious process. One-click chart generation through Excel was one of the first baby steps towards full automation. These day, entire databases and spreadsheets can be automatically visualized on the fly using software such as StatPlanet Cloud. Such tools and apps are becoming increasingly adept at understanding your data - including its structure, the different dimensions, and the meta data. This is key to automating data visualization. The current challenge is to automate the visualization of big data to determine big picture trends, but without losing sight of the details. Another challenge is knowing what the visualization is to be used for, and adapting it accordingly. Best practice visualization and design principles are important. But there also needs to be a match between the type of visualization and the purpose for which it will be used.


Interactivity has for a number of years been a key feature of online data visualization. But it is now starting to overtake static visualizations as the predominant way in which visualizations are presented - especially in news media. It is increasingly expected that every online graph, map and chart is interactive and/or animated. Users will want to switch between different types of visualizations, select and further explore areas of interest, and watch animations over time. The challenge of interactivity is to provide options catering to a broad range of users and corresponding requirements, without overcomplicating the user interface of the data visualization.

There are seven key types of interactivity,as described below. Most interactive visualizations we encounter online only support one or two of these. The envisioned future of visualization is one of increasing interactivity, providing additional, more powerful options of exploring and analyzing data visualizations:*

  • Selecting features: to highlight and emphasize areas of interest, to more easily identify them while exploring the visualization, and better analyze them
  • Explore: to explore different parts of the data set, such as by changing indicators or other dimensions of the data
  • Reconfigure: to re-arrange the data in the visualization
  • Encode: to change the type of visualization
  • Abstract/elaborate: to dig deeper and reveal more details, or to abstract or hide details
  • Filter: to restrict what is displayed in the data visualization according to certain conditions, such as a time range or a specific region within a map
  • Connect: to reveal relationships between items or features in the visualization

*Based on Yi, J. S., Kang, Y. A., Stasko, J., & Jacko, J. A. (2007). Toward a Deeper Understanding of the Role of Interaction in Information Visualization. IEEE Transactions on Visualization and Computer Graphics, 13(6), 1224-1231.

Storytelli​ng and VR

Storytelling with data is trendy, and rightfully so. Data visualizations are empty of meaning without a story, and stories can be greatly enriched when complemented with data visualization. The two go very well together. But what is still lacking is the tools which make it easy to link and integrate stories with different data visualization dimensions. For example, we need tools to more easily link stories to geographic and time dimensions within an interactive visualization. Eventually, software will be able to automate both data visualization and data interpretation, and even automate storytelling to a certain extent (much like the writing of certain types of news articles can be already be automated). But the future of storytelling may well be virtual reality. The human visual perception system is optimized to seeing and interacting in three dimensions. The full story telling potential of data visualization can be explored once it is no longer constrained to flat screens.