Moving beyond sequential design: Reflections on a rich multi-channel approach to data visualization

Wood, J., Beecham, R. &  Dykes, J.

We reflect on a four-year engagement with transport authorities and others involving a large dataset describing the use of a public bicycle-sharing scheme. We describe the role visualization of these data played in fostering engagement with policy makers, transport operators, the transport research community, the museum and gallery sector and the general public. We identify each of these as ‘channels’ – evolving relationships between producers and consumers of visualization – where traditional roles of the visualization expert and domain expert are blurred. In each case, we identify the different design decisions that were required to support each of these channels and the role played by the visualization process. Using chauffeured interaction with a flexible visual analytics system we demonstrate how insight was gained by policy makers into gendered spatio-temporal cycle behaviors, how this led to further insight into workplace commuting activity, group cycling behavior and explanations for street navigation choice. We demonstrate how this supported, and was supported by, the seemingly unrelated development of narrative-driven visualization via TEDx, of the creation and the setting of an art installation and the curating of digital and physical artefacts. We assert that existing models of visualization design, of tool/technique development and of insight generation do not adequately capture the richness of parallel engagement via these multiple channels of communication. We argue that developing multiple channels in parallel opens up opportunities for visualization design and analysis by building trust and authority and supporting creativity. This rich, non-sequential approach to visualization design is likely to foster serendipity, deepen insight and increase impact.

Citation and full paper:

Wood, J., Beecham, R. &  Dykes, J. (2014). Moving beyond sequential design: Reflections on a rich multi-channel approach to data visualization, IEEE Transactions on Visualization and Computer Graphics, 20(12).