Opt-in To The Lithuanian Collective Music Database

Listen Local Opt-In

Please use this link to opt-in to our experimental project.

What kind of data? What do you do with it?

More information about what data we collect from artists (or their representatives) and what we do with it can be found here

The Listen Local Opt-in Database is managed by the Listen Local and curators and the service development team. It empowers artists, or their authorized managers (artist managers or labels or publishers) to see what information is already available about the artist in various databases and internet sources, and to empower the artist to make corrections.

The primary aim of the opt-in database to make sure that algorithms which give visibility for the artist and manage payments for the use of the artist’s work perform these tasks seamlessly. The opt-in database fuels our services that connect the audience to new, relevant audiences and reveals new geographical and cultural market segments.

More information about the opt-in procedure and data handling here

We had conversations with other European artists on similar topics: OOPUS | Kurws | Bookie Baker | Jeremy Dunne | Katarzia | Twentees | Youniverse | Robin Kester | Marie de la Montagne | Damir Bašić aka Duka & with small companies and startups Tiny Rooms | LaPee | Flower of Sound | Hajde | From Rec to Play

Engage with Data&Lyrics on LinkedIn or @dataandlyrics! You can find our here open data and open repositories, code, tutorials.

Mark Adam Harold
Mark Adam Harold
Managing Director of MXF

Music and nightlife consultant specialising in public affairs and communications. Former City Councillor and Night Mayor of Vilnius, first elected immigrant in the history of Lithuania.

Gabija Liaugminaitė
Gabija Liaugminaitė
Digital service design

Cultural researcher with a passion for the world of music and ambitions to improve artists’ working and living conditions.

Daniel Antal
Daniel Antal
Data Scientist & Founder of the Digital Music Observatory

My research interests include reproducible social science, finance, and writing R packages.