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

Do the Shuffle: Exploring reasons for music listening through shuffled play

K.R. Sanfilippo, N. Spiro, M. Molina-Solana, A. Lamont

PLOS One 15 (2020), e0228457

DOI: 10.1371/journal.pone.0228457

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

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

Towards a large-scale twitter observatory for political events

S. Fernando, J. Amador, O. Serban, J. Gómez-Romero, M. Molina-Solana, Y. Guo

Future Generation Computer Systems (2020)

DOI: 10.1016/j.future.2019.10.013

TUORIS: A middleware for visualizing graphics in scalable resolution display environments

V. Martínez, S. Fernando, M. Molina-Solana, Y. Guo

Future Generation Computer Systems 106 (2020), 559-571

DOI: 10.1016/j.future.2020.01.015

Generalized regression hypothesis induction for energy consumption forecasting

R. Rueda, M. Pegalajar Cuellar, M. Molina-Solana, Y. Guo, M.C. Pegalajar

Energies 12 (2019), 1069

DOI: 10.3390/en12061069

A case study on understanding energy consumption through prediction and visualisation (VIMOEN)

L.G. Baca-Ruiz, M.C. Pegalajar, M. Molina-Solana, Y. Guo

Journal of Building Engineering 30 (2020), 101315

DOI: 10.1016/j.jobe.2020.101315