MDQS – Metadata Quality and Security: Holistic Data Validation and License Data Management in the Music Industry

Missing, inaccurate, or inconsistent metadata causes significant financial losses for rights holders in the music industry. The MDQS project explores a holistic approach to the automated validation and enrichment of metadata with the aim of sustainably improving metadata quality.

Holistic Validation of Data, Content, and Provenance

A key focus is the question of whether the simultaneous validation of material (file), content (musical work), description (metadata), and provenance (data sources and transmission paths) is feasible – and whether combining the individual validation results can generate new insights and added value.

In addition, MDQS addresses key aspects such as data security, data transparency, and the challenges posed by generative AI. The project applies AI-supported validation methods, fuzzy semantics, and blockchain-based smart contracts to improve data reliability and automate business processes. The approach is complemented by security measures such as Identity and Access Management and metadata anonymization.

Prototype and Transfer Potential

The project will result in a prototype demonstrating the practical feasibility of the approach within the music industry. At the same time, the project explores how its findings can be transferred to other sectors and applied to disinformation detection.

The project aims to research and test methods for comprehensive validation of the (meta)data that describe or are contained in a musical work (audio file), as well as to explore and evaluate approaches and methods for ensuring and improving data security.

Fraunhofer IDMT contributes its expertise particularly in the areas of music analysis, content and metadata matching, data modeling, media authentication, media security and data privacy, as well as synthesis detection.