Frequently Asked Questions

If you don’t find an answer for your question below, please contact the Fair MusE team at

Why should I share my music streaming data?

Your music listening data helps Fair MusE analyze how platforms and their algorithms work and influence consumers. This analysis is done with the goal to help create a fairer music industry in Europe through policies involving the governance of streaming platforms and copyright laws set by the EU.

Read our Research Manifesto and visit our website for more details.

When a sufficient number of users have shared their data, we will publish our Fairness Score visualisation on the fairness of the different streaming services, and a Music Dashboard.

What do I get out of sharing my data with the project?

First of all: You help the process of creating more fair conditions for music creators. This is the big perspective. This project focuses on providing some new insights and some numbers on fairness – or the lack of it. First of all, we need to find out what different people understand by ‘fairness’. We do that via interviews with users – you can participate here.

When you have uploaded your music, we also give you the possibility to study your own data, and compare it with other users’.

At you will be able to see your use of music visualised, and you will be able to compare it with the other users of Fair MusE. In this way we want to give something back.

What is the Fair MusE project about?

Fair MusE is a Horizon Europe research project (Grant number 101095088) that aims to make the music sector in Europe more efficient, more competitive, and more sustainable. The Fair MusE project seeks to shed light on how music algorithms, data collection, and exploitation models of social media and streaming platforms influence music creators and audiences. For more information, visit the homepage of our project.

The project started March 2023 and lasted for three years. The first two years are dedicated to the studies of 1) copyright legislation, 2) the economy of the music industry, and 3) algorithmic recommendation of music at streaming platforms. In the last year of the project we will find a synthesis between the three fields.

The Fair MusE project has two ‘sister’ projects: Music360 and OpenMusE, funded under the same funding scheme as Fair MusE.

How is my data being processed and protected?

We don’t show or share your music streaming data to anyone outside the Fair MusE project. We do not look into your data; we analyse it with different software tools we build ourselves to find patterns in how the algorithms recommend music.

Since your data is personal, we handle it under GDPR at secured servers. GDPR gives you data autonomy, allowing you to edit, request, and delete your data uploaded. Visit for more details.

Which users are we looking for?

We are looking for as many, and as diverse users of music streaming services, they just need to live in an EU country. If you know someone how would like to participate, please share with them!

How can I participate in an interview?

We want to know what your understanding of fairness is – and if fairness is relevant in music streaming services.

Therefore, we encourage you to sign up for an online interview with one of our researchers. We aim for making the interview in your language. The interview will take 20-30 minutes, and your answers will be anonymous.

Visit to sign up for an interview. The Fair MusE team will contact you to coordinate a time and platform of choice for the online interview.

Where and when can I see the outcome of the Fair MusE project?

As a Horizon EU project, Fair MusE has the responsibility to disseminate and share our results with the public. Fair MusE will continue to post on social media platforms and the Portal will contact you when there are new insights available regarding your music profile.  Visit for up to date news releases on publications and articles.
When a sufficient number of users have shared their data, we will publish our “Fairness Score” visualisation on the fairness of the different streaming services, and a “Music Dashboard”. As a first outcome we have written a report “Tuning In: A Comprehensive Analysis of Music Recommender Systems, Playlists, and Algorithmic Fairness”