Sonic Topographies of Abu Dhabi: Migrant Musical Worlds, Cultural Policy, and Urban Space — Data and Code

This repository accompanies the research project “Sonic Topographies of Abu Dhabi: Migrant Musical Worlds, Cultural Policy, and Urban Space”, and provides the data, code, and computational materials used for the analysis and visualization of urban soundscapes in Abu Dhabi. The project explores the relationships between migration, musical practices, and urban spatial dynamics in the Emirati context. It combines approaches from digital humanities, sound studies, and computational analysis to investigate how musical worlds emerge, circulate, and interact within a rapidly transforming urban environment shaped by cultural policy and global mobility. The repository includes: Data: curated datasets related to musical practices, spatial distribution, and cultural environments (or representative samples where data sharing is restricted); Code: Python scripts for generating visualizations and analytical outputs, including the file generate_visualizations.py; Notebooks: (if applicable) Jupyter/Colab notebooks supporting reproducibility and step-by-step analysis; Documentation: methodological notes, analytical materials, and a bibliography (Analysis_and_Bibliography.md); Research text: a full draft of the associated article in Markdown format. The computational pipeline supports the production of visual representations of sonic environments, enabling the exploration of spatialized musical activity and its relation to socio-cultural and institutional structures. Particular attention is given to reproducibility, transparency, and methodological clarity in line with current practices in digital humanities and computational social sciences. Due to ethical and legal considerations, some datasets may be partially anonymized or restricted. Where applicable, synthetic or reduced datasets are provided to allow replication of the analytical workflow. Reproducibility The code is written in Python and can be executed using standard scientific libraries. Instructions for installation and execution are provided in the README.md file. Users are encouraged to reproduce the visualizations and adapt the pipeline to other urban or cultural contexts. Related publication This dataset is associated with an academic article currently under preparation/submission. The Zenodo record ensures long-term accessibility, citability (via DOI), and versioning of the research outputs.