Digital Arabic Maqām Archive
Open-source interactive online platform and library for exploring the Arabic maqām system
About
The Digital Arabic Maqām Archive is an innovative open-access and open-source online platform dedicated to the study and exploration of the Arabic maqām system.
The platform is designed as a resource for students, musicians, composers, musicologists, educators, researchers, coders/developers, and anyone interested in the rich music theory of the Arabic-speaking region.
It offers an interactive and academically rigorous repository of tuning systems, ajnās, and maqāmāt, along with their suyūr (pathways of melodic development) and intiqālāt (modulations), all of which can be played and heard with a computer keyboard or via MIDI.
In addition, it provides in-depth mathematical data and analysis, comprehensive export options, an API and an NPM library for programmatic access to the data.
Core Features
Interactive Exploration
Play and hear hundreds of tuning systems, ajnās, and maqāmāt (on all their transpositions) using your computer keyboard or MIDI devices.
Comparative Analysis
Switch between multiple tuning systems to hear and compare their intervals on the same jins or maqām.
Mathematical Precision
Access detailed mathematical analysis including interval calculations, frequency ratios, cent values, string lengths, and ajnās constructions.
Algorithmic Modulations
Explore maqām modulation based on our unique algorithm created from Sāmī Al-Shawwā's rules for maqām modulation.
Scholarly Rigour
Access a comprehensive bibliography and source references for all the musicological data alongside analyses and commentaries.
Open Data Access
Export the data in various formats for research or creative use and access our open API or NPM library for programmatic integration.
Project Team
This project was researched, designed and developed by Khyam Allami and Ibrahim El Khansa in the Music Intelligence Lab at the American University of Beirut, Lebanon, and launched in September 2025.
Contribute
We welcome contributions from the community to help improve and expand this project further. Please visit our GitHub repository to report issues, suggest features, or submit pull requests. Alternatively, if you would like to help with data entry please get in touch with Khyam Allami directly on ka109@aub.edu.lb.