Description
We are witnessing an unprecedented exponential growth in the data that we create and that we are exposed to in our daily lives. This inevitable trend towards “Big Data” promises novel applications that could revolutionise business, administration, policy making, and science. While there is already extensive research on the early phases of the necessary data analysis pipeline, e.g., data cleansing, data mining, machine learning, sentiment analysis, there is much less work on how to communicate and present data towards the end of this pipeline in an accessible and interactive manner. This is problematic, since it is important that novel tools for data visualisation and analysis do not only empower a few selected data scientists but also the casual and non-expert users or society as a whole. I will show different examples from my work that demonstrate how the careful design of interaction techniques can substantially improve our human-data interaction with visualisations, for example by enabling groups of users to collaborate using visual-tangible user interfaces on interactive tabletops, by working seamlessly across many mobile screens in “bring your own device scenarios", or by using more physical and embodied interactions to increase users’ spatial memory and navigation performance. By this, I will illustrate how a combination of informatics, design, and controlled experiments with users can help us to achieve a much improved human-data interaction.| Period | 23 May 2016 |
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| Held at | University of Edinburgh, United Kingdom |