The Past, Present, and Future of Visualization Recommendation

TLDR: Visualization recommendation systems suggest useful insights to help users more effectively explore and understand their data. In this blog post, we examine a brief history of why these systems were developed, and where we are today, and outline open-challenges for future research.

This follows on nicely from the post above. What if the entire insight-generation process we have today—ask a question, formulate a query, select a chart, search for insight in it—could fundamentally change? What if, instead, a system were able to generate a large number of candidate visualizations from a subset of the data that you defined, and then present them to you in an interface, essentially asking the repeated question "Is this interesting?" The analyst's role becomes one of broadly defining a question topic and then swiping.

Don't get me wrong, this is not happening in the very near term. But it's ahistorical to assume that the current insight-generation workflow will remain static forever. Food for thought :D


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