Trustworthy AI and Data-Sharing Spaces for the Slovak Music Centre (Q3875): Difference between revisions
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Mesteranna (talk | contribs) (Created claim: creator (P124): Daniel Antal (Q3873)) |
Mesteranna (talk | contribs) (Created claim: has time (P99): 23 November 2024) |
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Revision as of 08:47, 19 December 2025
This poster, Trustworthy AI and Data-Sharing Spaces for the Slovak Music Centre, was presented at the IAMIC Conference 2024 on November 21, 2024, at Music Austria, Vienna. It explores how collective management organisations (CMOs) and music information centres (MICs) can adapt to the algorithm-driven discovery era by adopting modern data enrichment and federation practices. The Slovak Comprehensive Music Database (SKCMDb) serves as a case study for building a national, interoperable data-sharing space aligned with the European Interoperability Framework (EIF) and the European Collaborative Cloud for Cultural Heritage (ECCCH). The poster outlines strategies for integrating public and private data, mitigating algorithmic bias through “trustworthy AI,” and federating regional or genre-specific music data spaces into a decentralized European Music Observatory.
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Trustworthy AI and Data-Sharing Spaces for the Slovak Music Centre |
This poster, Trustworthy AI and Data-Sharing Spaces for the Slovak Music Centre, was presented at the IAMIC Conference 2024 on November 21, 2024, at Music Austria, Vienna. It explores how collective management organisations (CMOs) and music information centres (MICs) can adapt to the algorithm-driven discovery era by adopting modern data enrichment and federation practices. The Slovak Comprehensive Music Database (SKCMDb) serves as a case study for building a national, interoperable data-sharing space aligned with the European Interoperability Framework (EIF) and the European Collaborative Cloud for Cultural Heritage (ECCCH). The poster outlines strategies for integrating public and private data, mitigating algorithmic bias through “trustworthy AI,” and federating regional or genre-specific music data spaces into a decentralized European Music Observatory. |