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Authoring Data-Driven Videos with DataClips

Data videos, or short data-driven motion graphics, are an increasingly popular medium for storytelling. However, creating data videos is difficult as it involves pulling together a unique combination of skills. We introduce DataClips, an authoring tool aimed at lowering the barriers to crafting data videos. DataClips allows non-experts to assemble data-driven “clips” together to form longer sequences. We constructed the library of data clips by analyzing the composition of over 70 data videos produced by reputable sources such as The New York Times and The Guardian. We demonstrate that DataClips can reproduce over 90% of our data videos corpus. We also report on a qualitative study comparing the authoring process and outcome achieved by (1) non-experts using DataClips, and (2) experts using Adobe Illustrator and After Effects to create data-driven clips. Results indicated that non-experts are able to learn and use DataClips with a short training period. In the span of one hour, they were able to produce more videos than experts using a professional editing tool, and their clips were rated similarly by an independent audience.

F. Amini, N. H. Riche, B. Lee, A. M. Hernández, and P. Irani. Authoring Data-Driven Videos with DataClips. To appear in IEEE Transactions on Visualization and Computer Graphics, InfoVis 2016.

Authors

Fereshteh Amini

Fereshteh Amini

PhD Student
Pourang Irani

Pourang Irani

Professor
Canada Research Chair

As well as: Nathalie Henry Riche, Bongshin Lee, and Andrés Monroy-Hernández