Projects

We would like to present the concept and a demo of a Finno-Ugric Data Sharing Space as a knowledge base and a trustworthy AI application, and a replication of our Slovak Comprehensive Music Database created with a data sharing space in 2020-2024.

Download our feasibility study from https://doi.org/10.5281/zenodo.6427514. In 2020, we studied the effect of increasingly AI-driven streaming platforms on the Slovak music repertoire. We realised that music is being recommended by algorithms, not only to YouTube or Spotify subscribers but also to radio editors, concert promoters, and festival organisers.

We bring data-, sustainability-, rights management innovation, and novel distribution models nearer to the grassroots level of creation.

OpenMuse brings together music industry stakeholders and researchers from 12 European countries. Our partners represent the diversity of the industry, as well as the shared need to find financially, socially, and environmentally sustainable policy and business models in multiple, sometimes-fragmented streams (e.g., live music, composers/publishers, and recordings with producers and performers).

We will help small music organizations in their sustainability reporting, where detail data and reporting standards are only available for greenhouse gas emissions.

We will help small music organizations in their sustainability reporting, where detail data and reporting standards are only available for greenhouse gas emissions.

Open Policy Analysis is an approach to policy analysis wherein data, code, materials, and clear accounts of methodological decisions are made freely available to facilitate collaboration, discussion, and reuse.

Open Music Europe brings together music industry stakeholders and researchers from 12 European countries. Our partners represent the diversity of the industry, as well as the shared need to find financially, socially, and environmentally sustainable policy and business models in multiple, sometimes-fragmented streams (e.g., live music, composers/publishers, and recordings with producers and performers).

Listen Local is a trustworthy, ethical AI-powered system that aims to help great artists in small organizations and small countries using big data. We want to make sure that audiences are not only recommended global superhits, but locally relevant music, too. At present, corporate algorithms fail to connect listeners in small countries with music from the local scene - with artists whom the listener can easily see perform live in local venues, who sing in the listener’s language and who connect with the listener’s feelings and experiences.

Our Digital Music Observatory contributed to the Music Creators’ Earnings in the Streaming Era project with understanding the level of justified and unjustified differences in rightsholder earnings, and putting them into a broader music economy context. The entire research paper is published by the UK Intellectual Property office, and we made the details of our analysis available in a joint publication.