The 5th edition of MusicLab was an algorave (algorithmic rave) featuring Renick Bell based in Japan, Khoparzi based in India, and researchers in Norway. Renick Bell and Khoparzi live-streamed improvised live-coded music on their computers while the audience danced at home. We measured audience members' movement using our new MusicLab mobile application that uses smartphones' accelerometers and gyroscopes. We also asked questions about the experience of the concert.
Learn more from the webpage. The video of the concert, panel discussion, and data jockeying can be viewed here. Raw data can be downloaded here.
This repository contains the data jockeying notebook by Cagri Erdem and building on Cagri's work, Dana Swarbrick conducted the data analysis on the MusicLab IMU data for RPPW2021. You can watch the video here. The data was also presented at ICMPC ESCOM 2021.
- MusicLab5_DJ.ipynb - Cagri's data jockeying notebook
- MusicLab5_DataAnalysis_20210610.ipynb - built on Cagri's notebook but to enable looping through the motion files of each participant.
- MusicLab5_DataAnalysis_ExtractPerformances_20210611.ipynb - script to identify the start of the performances in the motion data using ginput (manual identification of the start of the music.
- MusicLab5_DataAnalysis_Animations_20210614.ipynb - script to create animations from the motion data.
- MusicLab5_DataAnalysis_Filtering_20210617.ipynb - script to conduct filtering.
- MusicLab5_DataAnalysis_Geolocation_20210707.ipynb - script to analyze, anonymize, and visualize geolocation.
- MusicLab5_DataAnalysis_SMC22.ipynb contains the analyses for the SMC2022 peer-reviewed conference paper
Note: Sometimes the code refers to Dana (experimenter) and Solveig (host) as participants however, they were not included in any analyses and simply used the application for testing purposes.
This work was presented in a paper in SMC2022. The script MusicLab5_DataAnalysis_SMC22.ipynb contains the analyses for this paper that builds upon the other notebooks.