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Interactive Evolution of Swarms for the Visualisation of Consumptions

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Abstract

Information Visualisation studies how visual representations can help understanding hidden patterns in large amounts of data. The produced visual artefacts should have both functional and aesthetic dimensions to make the visualisation appealing to the user. However, in the Data Aesthetics field, the process of creation of visualisations is more concerned with aesthetics. Our goal for this project is to develop a framework to explore the aesthetic dimension of a functional visualisation model characterised by a series of parameters, which can make the visualisation more functional or more aesthetically appealing. In concrete, we propose a framework based on Interactive Evolutionary Computation (iec) to evolve the parameterisation of the visualisation model, enabling the user to explore new possibilities and to create different aesthetics over the data. Our case study will be a dataset with the consumption patterns of the Portuguese people in one retail company. The developed system is able to create a wide diversity of emergent visual artefacts that can be intriguing and aesthetically appealing for the user.

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Notes

  1. 1.

    A video of this interface can be seen in: https://vimeo.com/289093672.

  2. 2.

    In https://cdv.dei.uc.pt/ie-of-swarms-in-visualisation it is possible to see other visual solutions.

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Acknowledgements

The first author is funded by Fundação para a Ciência e Tecnologia (FCT), Portugal, under the grant SFRH/BD/129481/2017.

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Correspondence to Catarina Maçãs .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Maçãs, C., Lourenço, N., Machado, P. (2019). Interactive Evolution of Swarms for the Visualisation of Consumptions. In: Brooks, A., Brooks, E., Sylla, C. (eds) Interactivity, Game Creation, Design, Learning, and Innovation. ArtsIT DLI 2018 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 265. Springer, Cham. https://doi.org/10.1007/978-3-030-06134-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-06134-0_11

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