Maps Not Lists: Network Graphs for Data Exploration

Design Ballroom CD
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The majority of data we consume today are presented in lists, for example search results, news feeds, and recommendations. The makers of these lists get to decide what’s at the top, and while that can be useful for quick filtering, it is very limiting for understanding context or for thinking strategically.

Public health officials confronting epidemics and generals planning battles interact with geographic maps to explore all the possible plans of attack. However, for decision makers facing conceptual complexity geography isn’t necessarily the right organizing principle, and so new types of maps are needed to enable them to explore multiple dimensions. This could be a business strategist trying to outmaneuver their competitor, or a technologist understanding how new scientific advances could change their field.

This talk explores the use of network graphs as maps of rich datasets. We’ll look at how unstructured data can be represented as nodes and edges using similarity metrics, how learnings from cartography inform their design and interactivity, and the toolkits available to make your own. In the process we’ll see what these maps can teach us about the evolution of big data itself.

Photo of Amy Heineike

Amy Heineike


Amy is the Director of Mathematics at Quid, where she has been since its inception, prototyping and launching the company’s technology for analyzing document sets. A Cambridge Mathematician who previously worked in London modeling cities, Amy is fascinated by complex human systems, and the algorithms and data that help us understand them.


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