Visualisation and user experience

Reporting on Task 2.3 activities aimed at: • Develop visual metaphors able to create synergies between the human cognition and the artificial computation. • Develop of Semantic Interaction solutions, i.e. approaches in which data are visualised in an interactive form, and the user's analytical reasoning is inferred and in turn used to steer the underlying models (Endert et al., 2012a, b; Endert et al., 2014). This can be initially achieved by coupling different controls to the parameters of the visual representation, as the parameters of the underlying analytic models are represented by the constructs of the visualisation, tacit knowledge of the user's reasoning can be inferred through inverting these analytic models. Semantic interaction also allows a more direct interaction with the information; and the creation of sets of optimal inputs, which once inserted in the system, would produce the output desired by the user in his/her explorations. • Visual data exploration aims at the integration of the human in the data exploration process. Leveraging on human perceptual abilities, visual data exploration is especially useful when little is known about the data and the exploration goals are vague (Andrienko and Andrienko, 1999; Keim, 2001). While the visual exploration can in principle be complemented by other automatic techniques, a framework for such integration is still missing and needs to be addressed. Visual exploration can easily deal with highly heterogeneous and noisy data, and has the advantage of requiring no understanding of complex mathematical and statistical algorithms. • Provide both intelligently summarised fast-access reporting as well as more detailed in-depth reporting. Another aspect to be addressed is the prioritisation and ontological structuring of data, information and knowledge and the advanced ability to include certain trade-off comparisons in the visualisation layout concept for more holistic decision-making purposes.