The Role of Visualization in the Big Data Era: An End to a Means or a Means to an End?


While interpretations of the term big data vary across different stakeholders, there is no denying the fact we live in the era of big, complex, and rich data. This presents obvious opportunities to visualization for tapping into the analytical value of the data. Being a relatively nascent field compared to its exploratory data analysis siblings: statistics, machine learning, data mining, etc., there is a need for introspection into how visualization can best fit into the big data analysis pipeline. In this pipeline, while infrastructure building for big data has received most of the attention, much less focus has been on devising ways to improve interpretation of such complex data. We believe, by introspecting on the role of visualization in the big data era, we can achieve a two-fold purpose: i) highlight the visualization-specific challenges for handling big data and chart out a roadmap for the immediate future, and ii) establish visualization as a first-class citizen in the big data pipeline and thereby make a significant impact on the state-of-the-art of interpretation and analysis of such complex data.
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Aritra Dasgupta, Danyel Fisher, Carlos Scheidegger, Daniel Keim, Robert Kosara, Heidi Lam,
The Role of Visualization in the Big Data Era: An End to a Means or a Means to an End?,
IEEE VIS Panel, 2013.