DATASOUND

A H2020 project by Miguel Molina-Solana.

More and more, organizations are generating huge amounts of data, which need to be stored and processed in order to gain useful insights and achieve competitive advantage. While the storage and analysis are nowadays mostly carried out by computers, the interpretation of data is still performed by humans through visual means. This research project proposes a novel and complementary approach to data interpretation by means of sound, and aims to address the scientific question of “Can sound be used for Data Science?”. Its results will be of relevance to identify patterns in real-time continuous data, and it will be tested in the context of real-time energy monitoring in a building.

Publications

Visualizing large knowledge graphs: A performance analysis

J. Gómez-Romero, M. Molina-Solana, A. Oehmichen, Y. Guo

Future Generation Computer Systems 89 (2018), 224-238

DOI: 10.1016/j.future.2018.06.015

The improvisational state of mind: a multidisciplinary study of an improvisatory approach to classical music repertoire performance

D. Dolan, H.J. Jensen, P. Martinez-Mediano, M. Molina-Solana, H. Rajpal, F. Rosas, J.A. Sloboda

Frontiers in Psychology 9 (2018), 1341

DOI: 10.3389/fpsyg.2018.01341