Abstract
This article presents our interaction design for DataChopin, based on an extensive survey and classification of visualisation for exploratory data analysis. Its distinctive characteristics are the use of a large-scale display wall as a shared desktop, as well as flexible composition mechanisms for incremental and piece-wise construction of visualisations. We chose composability as a guiding principle in our design, since it is essential to open-ended exploration, as well as collaborative analysis. For one, it enables truly exploratory inquiry by letting users freely examine different combinations of data, rather than offering a predetermined set of choices. Perhaps more importantly, it provides a foundation for data analysis through collaborative interaction with visualisations. If data and visualisations are composable, they can split into independent parts and recombined during the analytical process, allowing analysts to seamlessly transition between closely- and loosely-coupled work.
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Acknowledgments
We would like to thank the Visualisation and eResearch (ViseR) team at QUT for their technical support. Illustrations in this article contain icons by GestureWorks, released under CC BY-SA.
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Filonik, D., Rittenbruch, M., Foth, M. (2016). DataChopin - Designing Interactions for Visualisation Composition in a Co-Located, Cooperative Environment. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2016. Lecture Notes in Computer Science(), vol 9929. Springer, Cham. https://doi.org/10.1007/978-3-319-46771-9_17
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DOI: https://doi.org/10.1007/978-3-319-46771-9_17
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