2  Background & Concept

This chapter provides the historical, conceptual, and policy foundations needed to understand why and how the Open Music Europe project operates through a unified data-to-policy pipeline, and why the Open Music Observatory (OMO) and the Open Music Europe Data Management Plan (DMP) form the backbone of that pipeline.

It first explains the origins of the European Music Observatory idea, tracing the policy dialogue from Music Moves Europe and the 2018 EMO Feasibility Study to the decentralised CEEMID initiative, which anticipated many of the technical and governance principles later adopted by the EU’s data-space strategy. It then situates Open Music Europe within the evolving European policy environment: the European Parliament’s resolutions, the EU Music Ecosystem Study, the emergence of sectoral data spaces, and alignment with Europeana, EOSC/ECCCH, and the EU Open Data Portal.

This context is essential for understanding why the Observatory must be federated, decentralised, interoperable, and automated, and why a traditional centralised observatory model is no longer viable.

You can visit the Open Music Observatory on https://openmusicobservatory.eu/. For API-level access get in touch with Reprex.

From the outset of this work, we have taken the view that Europe should avoid building siloed cultural data infrastructures by domain. Wherever possible, cultural data should be shared across domains through common principles, identifiers, and governance frameworks. Domain-specific solutions should emerge only where generic infrastructures reach their limits.

Music is one of the domains where these limits are reached earliest and most visibly.

NotePolicy Context: The Open Music Europe Green Paper

The Green Paper on AI, Data Governance, and Metadata Policies for Europe’s Music Ecosystem provides the broader policy framework for the Open Music Observatory.
It explains:

  • how the data-to-policy pipeline aligns with the EU’s European Strategy for Data,
  • how OMO’s federated architecture reflects the principles of the Data Governance Act, Data Act, and the Data Spaces Support Centre (DSSC),
  • how metadata governance interacts with AI policies (AI Act, Trustworthy AI Guidelines, cultural-sector risk considerations), and
  • how OMO supports emerging reforms in copyright infrastructures, especially where attribution, identifiers, and lifecycle metadata intersect.

The Green Paper also integrates insights from the CITF First Project Report (2025), showing how music-sector data spaces complement cross-sector requirements for trustworthy, machine-readable rights metadata.

Together with the OMO technical documentation and the Data Management Plan, the Green Paper forms the policy and governance layer of the Observatory’s design.

Finally, the chapter introduces the Open Music Europe data-to-policy pipeline—the core methodological mechanism defined in the Grant Agreement as “an open, scalable data-to-policy pipeline for European music ecosystems.” The pipeline structures all project activities (WP1–WP5) and provides the operational logic of the Observatory. It links:

all under the governance framework established by the DMP.

Taken together, these elements explain the rationale behind the OMO architecture, its dataspace foundations, and the methodological choices documented in the remainder of the report.

2.1 Why Europe Needs a Music Observatory

In late 2015, the European Commission began a structured dialogue with representatives of the music sector1 to identify key challenges and possible forms of EU support. Under the Music Moves Europe programme, the Commission launched the 2018 Preparatory Action Boosting European Music Diversity and Talent, which produced the Feasibility Study for the Establishment of a European Music Observatory (European Commission et al. 2020).

The Open Music Observatory is not a greenfield initiative. It represents the continuation and formalisation of CEEMID (Central European Entertainment and Media Industry Databases), a decentralised music data integration system developed by the authors in collaboration with partners in Central Europe. CEEMID emerged in response to structural data gaps in smaller and medium-sized music markets and demonstrated that interoperable, reproducible music indicators could be produced without centralising data ownership. This experience directly informed the design principles of the Open Music Observatory.

The European Commission’s feasibility study for the establishment of a European Music Observatory explicitly highlighted CEEMID as a best-practice example of decentralised, open, and reproducible music data integration, recommending that its approach be further explored during the start-up phase of a future Observatory2. The Open Music Observatory can therefore be understood as a direct response to this recommendation, updated to reflect subsequent European data space, copyright infrastructure, and AI policy developments.

The later CITF First Project Report (2025) independently identified similar structural obstacles across copyright-dependent sectors: fragmented identifiers, inconsistencies in rights metadata, and the absence of lifecycle-aware registries. This convergence strengthens the evidence base for an Observatory design rooted in federation, interoperability, and transparent provenance.

The Feasibility Study identified 45 data gaps that impede the development of evidence-based policies for competitiveness, value creation, diversity, and employment in the European music ecosystem. It highlighted that:

“Data collection in Eastern and Southern Europe is lagging in comparison to other European Member States in Northern and Western Europe… These data conditions and the problems they present for effective management and policy development are the fundamental reasons for supporting the creation of a European Music Observatory.” (European Commission et al. 2020, p9–10)

The study explicitly mentioned CEEMID as a promising bottom-up model for filling these gaps and providing a more modern, decentralised alternative to traditional observatory structures (Artisjus et al. 2014).

The Feasibility Study also provided a clear definition of the stakeholders that a future European Music Observatory must serve. It distinguished three groups whose information needs and policy roles must be supported:

  • Industry: commercial organisations and agents involved in income-generating activities across performance, recording, distribution, and creation.
  • Civic: policymakers, NGOs, professional associations, and publicly funded intermediaries whose decisions shape the regulatory and support environment.
  • Public: consumers, cultural participants, education and training institutions, and third-sector organisations interested in the wider social and cultural roles of music.

See (European Commission et al. 2020, p30)

These stakeholder categories continue to structure the Observatory’s service model and interoperability requirements.

2.2 Historical Precedent: CEEMID

The former CEEMID (originally: Central & Eastern European Music Industry Databases) collaboration began in 2014 as a voluntary, decentralised data initiative created by three collective management societies. Over time, it grew to include more than 60 stakeholders in 12 European countries. Its purpose was to fill the most pressing evidence gaps by combining:

  • voluntary data integration among partners,
  • open-data reprocessing, and
  • co-financed data collection.

This work is documented in (Antal 2020).

CEEMID operated according to principles that would later become central to the European Union’s data (sharing) space strategy (formalised only years later). Its decentralised organisational model, distributed data stewardship, and emphasis on transparent, reusable methods demonstrated that a modern observatory in the digital era does not need to be a centralised institution. Instead, it can function as a federated ecosystem connecting statistical offices, cultural institutions, CMOs, and private actors.

Long before the EU formalised its dataspace strategy, CEEMID also aligned its workflows with emerging statistical-system standards such as GSIM, DDI, and SDMX, anticipating later European requirements for interoperable, machine-readable statistical metadata. This early adoption provided a methodological bridge between cultural-sector data, administrative registers, and official statistics, and formed a direct precursor to the metadata foundations of the Open Music Observatory.

The Feasibility Study for the European Music Observatory explicitly recognised CEEMID as a potential building block for a new observatory model. Our proposal therefore sought to transform CEEMID’s prototype—referred to in the study as the Digital Music Observatory—into a scientifically robust and methodologically coherent system that could scale across Europe. This required grounding the work in state-of-the-art statistical science, data science, and computer science, and ensuring alignment with European interoperability and data-governance frameworks.

The prototype work that preceded Open Music Europe was shaped through two innovation environments: the Yes!Delft AI+Blockchain Lab, where product–market fit and technical feasibility were tested, and the JUMP Music Market Accelerator, where the first integrated prototype of a Digital Music Observatory was developed. These early iterations validated not only stakeholder demand but also the feasibility of a decentralised, standards-based architecture, and they informed the methodological and technical design choices taken forward in this project.

2.3 Policy and Technological Evolution Enabling a New Observatory

Since the publication of the EMO Feasibility Study, the European Union has introduced a series of policy and infrastructure initiatives that strengthen the case for a decentralised, interoperable, and federated European Music Observatory. These developments span European Parliament mandates, Commission-funded research, cultural-heritage clouds, open-data regulation, and the EU’s overarching data-space strategy. Together, they establish the policy and technological foundations on which the Open Music Observatory is built.

Our policy alignment is discussed in more detail in - Music Metadata Mainstreaming and EU Law - A Green Paper on AI, Data Governance, and Metadata–Policies for Europe’s Music Ecosystem3

2.3.1 European Parliament and EU-level Mandates

The European Parliament, in its resolutions on the future of the music sector, explicitly called for:

  • the establishment of a European Music Observatory,
  • improved evidence for competitiveness, diversity, and fair remuneration, and
  • stronger coordination of public, private, and community data sources.

These mandates update and reinforce both the Music Moves Europe framework and the findings of the EMO Feasibility Study. They frame the Observatory as an instrument that must serve industry, civic, and public actors through interoperable, reusable, cross-border data services.

The EU Music Ecosystem Study (2025) deepened this diagnosis, pointing to fragmentation across metadata, rights information, cultural statistics, and market data. It concluded that the sector requires a technical and governance model capable of linking these domains, rather than separate, siloed initiatives. The architecture of our dataspace responds directly to these recommendations.

The European Parliament has rightly highlighted that fragmented and unreliable metadata remains a major obstacle in the music sector. European Parliament Resolution of 17 January 2024 on Cultural Diversity and the Conditions for Authors in the European Music Streaming Market

  1. Emphasises that it is essential to improve the identification of anyone involved in the creation process, in particular authors and performers, on music streaming services, by ensuring the comprehensive and accurate allocation of metadata from the time of Directive 2014/26/EU of the European Parliament and of the Council of 26 February 2014 on collective management of copyright and related rights and multiterritorial licensing of rights in musical works for online use in the internal market (OJ L 84, 20.3.2014, p. 72). creation for any track uploaded to a music streaming service; encourages, in this regard, the use of all international identification codes (IPI, ISWC, ISRC, IPN, and ISNI); highlights that proper identification of creators plays a key role in the search for and discoverability of works, and enables proper remuneration for creators in the distribution of revenues.

Our Observatory’s distributed model directly answers European Parliament’s call for metadata systems that are reliable, inclusive, and supportive of creators. Our policy alignment is explained in detail in our our policy paper, A Green Paper on AI, Data Governance, and Metadata Policies for Europe’s Music Ecosystem4.

2.3.2 Data (Sharing) Spaces

The EU’s adoption of data (sharing) spaces provides the organisational and legal model for an Observatory that is not a centralised institution but a federated ecosystem.

Curry defines dataspaces as:

“an emerging approach to data management… Data is integrated on an ‘as-needed’ basis, with the labour-intensive aspects of data integration postponed until they are required.” (Curry 2020)

The Design Principles for Data Spaces position paper further describes them as:

“a federated data ecosystem within a certain application domain and based on shared policies and rules.” (Nagel and Lycklama 2021, p7)

These principles are fully consistent with CEEMID’s decentralised model and form the conceptual basis for the Open Music Dataspace (see Chapter 5).

The CITF (2025) report arrives at the same architectural conclusion. It stresses that trustworthy copyright infrastructures in the AI era require federated governance, interoperable identifiers, and verifiable provenance chains rather than a single, centralised registry. Its three-layer model—foundational identifiers, shared semantics, and technical services—maps closely onto the Observatory’s dataspace design.

Observatories created in the 1990s and early 2000s were built around centralised databases and slow-moving data-collection cycles. Since then, the rapid expansion of agentic AI in data collection, the widespread digitisation of live and recorded music, and the proliferation of large-scale, real-time data sources have made such centralised architectures obsolete. Modern evidence ecosystems require automated ingestion, continuous semantic enrichment, cross-domain reconciliation, and transparent provenance — all of which presuppose a federated, decentralised model rather than a single institutional database.

The European Audiovisual Observatory (EAO), the European Market Observatory for Fisheries and Aquaculture Products (EUMOFA), and the European Observatory on Infringements of Intellectual Property Rights (EUIPO) provide valuable models of long-standing EU observatories. However, each operates within a centralised data-submission and aggregation framework appropriate to their legal mandates and sectoral data structures. The Feasibility Study acknowledged that the music sector lacks comparable legal obligations and contains far more fragmented, cross-domain, multilingual, and institutionally diverse datasets. Therefore, while these observatories offer important governance precedents, their centralised architectures cannot be replicated in the music ecosystem — strengthening the case for a federated dataspace model.

2.3.3 Preference for Open-Source and Open Standards in the EU

Across the EU’s data and digital-transition strategies, there is a consistent preference for:

  • open-source software,
  • open standards,
  • open licensing, and
  • transparent, reproducible workflows.

This aligns directly with the Observatory’s use of open-source R and Python pipelines, Wikibase for semantic interoperability, and FAIR-compliant metadata.

2.3.4 Alignment with Europeana and Cultural Heritage Infrastructures

Europeana demonstrates how Europe manages distributed cultural-haritage collections at scale using:

  • persistent identifiers,
  • multilingual metadata,
  • open licences (e.g. CC BY),
  • shared semantic standards (EDM, IIIF, rightsstatements.org), and
  • decentralised stewardship by libraries, archives, and museums.

The Open Music Observatory follows the same principles. It uses:

  • semantic technologies,
  • PID-based cross-domain linking, and
  • open, reusable data models.

This ensures interoperability with cultural-heritage collections, performing-arts archives, and national memory institutions, and aligns the music domain with the emerging European Collaborative Cloud for Cultural Heritage (ECCCH).

2.3.5 Alignment with the EU Open Data Portal and EU Open Data Strategy

The EU Open Data Portal (data.europa.eu) establishes a common framework for:

  • open licences (e.g. CC BY 4.0),
  • machine-readable formats,
  • harmonised metadata (DCAT-AP),
  • and publication of public-sector information.

The Open Music Observatory is designed so that:

  • public datasets can be harvested directly by the EU Open Data Portal,
  • indicators and derived datasets comply with open-data rules, and
  • metadata follow DCAT-AP and DataCite to support long-term reuse.

This alignment ensures that the Observatory meets both Horizon Europe open-science requirements and broader EU open-data policy objectives.

2.3.6 European Interoperability Framework (EIF)

The European Interoperability Framework (EIF) provides a four-layer model—legal, organisational, semantic, technical—for connecting:

  • public authorities,
  • cultural institutions,
  • rights-management organisations,
  • national statistical offices, and
  • private intermediaries.

These are precisely the actors whose data must interoperate to support a European Music Observatory. By adopting the EIF, the Observatory can link diverse datasets into coherent, reusable services without centralising them.

2.3.7 EOSC and ECCCH: Open Science and Cultural-Heritage Clouds

The European Open Science Cloud (EOSC) and the European Collaborative Cloud for Cultural Heritage (ECCCH) promote:

  • FAIR data,
  • open science workflows,
  • reproducible analysis,
  • transparent provenance, and
  • decentralised storage and processing.

These principles inform the Observatory’s architecture through the use of:

  • open-source analytical pipelines,
  • SDMX and DataCite metadata,
  • persistent identifiers, and
  • federated linking across domains and institutions.

2.3.8 Summary

Together, these EU policy instruments—the Parliament’s mandate, the EU Music Ecosystem Study, data-space strategy, Europeana, the EU Open Data Portal, the EIF, EOSC, and ECCCH—provide a unified rationale for an Observatory that is federated, decentralised, data-driven, and interoperable by design. They define the policy and technological environment in which the Open Music Observatory must operate and directly shape its architecture. The Chapter 4 explains why we chose an architecture that is built around Wikibase and Wikiadta.

2.4 Why Open Music Europe Uses a Decentralised Dataspace Model

The Open Music Observatory adopts a decentralised, federated dataspace model because this is the only architecture that meets the needs identified by the EMO Feasibility Study, the EU Music Ecosystem Study, and the European Parliament’s resolutions, while also complying with the newer EU frameworks for interoperability, data governance, and cultural-heritage infrastructures. A centralised database model, common in observatories built in the 1990s or early 2000s, is no longer feasible or desirable for the music sector.

2.4.1 Lessons from CEEMID

The CEEMID collaboration demonstrated that most music-sector data—repertoire, rights, cultural-heritage descriptions, business metadata, and statistical evidence—originate from many different institutions, each with its own mandates, legal obligations, and technical systems. Centralising such data is:

  • legally constrained (e.g. GDPR, contractual confidentiality),
  • institutionally unrealistic (distributed ownership and stewardship), and
  • technically inefficient (rapidly evolving local systems).

CEEMID showed that these data can nonetheless be made interoperable through:

  • shared identifiers and authority files,
  • open metadata standards,
  • reproducible R-based pipelines, and
  • rule-based, voluntary data sharing.

These are the foundational principles of a data (sharing) space, which the EU has since elevated to a core strategic component of its digital-policy agenda.

2.4.2 Requirements of the EU policy environment

As outlined in Section C, the EU now expects cultural and creative sectors to adopt:

  • federated data architectures,
  • FAIR and open data practices,
  • transparent governance models,
  • semantic interoperability, and
  • alignment with Europeana, EOSC, ECCCH, and data.europa.eu.

This expectation reflects the broader transformation of European data governance, where sectors are encouraged to organise around data spaces rather than central repositories. A decentralised model also supports cultural and data sovereignty by allowing institutions to maintain control over their collections and data-processing rules.

2.4.3 Requirements of the Grant Agreement

The Open Music Europe Grant Agreement defines the project explicitly as:

“an open, scalable data-to-policy pipeline for European music ecosystems”

and mandates the creation of:

“a highly automated, decentralised intelligence hub that aggregates open data and creates dynamic, live policy documents.”

To fulfil these contractual obligations, the Observatory must:

  • connect heterogeneous data sources without centralising them,
  • refresh indicators automatically as upstream data changes,
  • maintain legally sound provenance across many institutions,
  • support multilingual, cross-border metadata, and
  • integrate statistical, cultural-heritage, and industry systems.

These requirements can only be met in a federated dataspace, not in a single, centralised database.

2.4.4 Technical rationale for decentralisation

The dataspace model makes it possible to:

  • keep sensitive or personal data (e.g. rights, royalties) within the institution that controls them,
  • link sources through semantic federation (Wikibase/Wikidata),
  • enable distributed curation by librarians, archivists, CMOs, and researchers,
  • integrate permanent identifier (PID) systems across domains (ISNI, VIAF, ROR, company registers),
  • use open standards (SDMX, DDI, DataCite, DCAT-AP), and
  • scale to new partners, genres, languages, and Member States.

This structure mirrors the actual distribution of data in the music sector and the technical direction of the EU’s digital transition.

Recent research highlights how music discovery is increasingly shaped by opaque, platform-controlled recommendation systems that structure visibility, attention, and cultural participation. These systems exert measurable influence on user behaviour, commercial outcomes, and the availability of minority or non-mainstream repertoires, yet they remain largely inaccessible to independent scrutiny. The argument that public-interest infrastructures must provide transparent, auditable, and diversity-preserving alternatives aligns directly with the rationale for a decentralised European Music Observatory. By foregrounding metadata quality, open workflow documentation, and federated governance, the Observatory responds to concerns that current algorithmic environments reproduce structural asymmetries and limit cultural plurality (Guest, Suarez, and Rooij 2025).

2.4.5 Why decentralisation is essential for a European Music Observatory

For the European music ecosystem, decentralisation enables:

  • lower administrative and compliance burdens,
  • institutional autonomy and data sovereignty,
  • cross-border comparability without forced data transfer,
  • community- and expert-driven metadata improvement,
  • GDPR-compliant handling of personal data, and
  • sustainable expansion of the Observatory.

A decentralised dataspace is therefore not an architectural choice but a necessary governance model for an Observatory that spans cultural heritage, rights management, statistical registers, community archives, and private-sector metadata across the EU.

The Open Music Observatory is consequently designed as a federated, rule-based dataspace: an ecosystem where public, private, and civic stakeholders contribute knowledge, maintain authority records, and generate indicators while preserving full control over their own data.

2.5 The Data-to-Policy Pipeline: How Open Music Europe Works

The Open Music Europe action is contractually defined as “an open, scalable data-to-policy pipeline for European music ecosystems” (see Grant Agreement). This is not a slogan: it is the methodological core of the project and the organising principle of all work packages (WP1–WP5). The pipeline connects indicator design, data governance, data acquisition, semantic modelling, statistical analysis, and policy translation into a single reproducible workflow. This chapter introduces the logic of that pipeline and explains how it shapes the design of the Open Music Observatory.

2.5.1 1. Indicator and problem definition (WP1–WP3)

Each thematic work package begins by identifying policy-relevant gaps and defining the indicators needed to address them. Deliverables D1.1, D2.1, and D3.1 specify:

  • the conceptual frameworks guiding each domain (economy, diversity, society),
  • the data requirements for measuring them, and
  • the procedures for ensuring comparability across countries and years.

These definitions also appear in the Open Music Europe Data Management Plan (D6.3), which provides human-readable summaries and machine-readable metadata for all indicators.

2.5.2 2. Data governance (WP1–WP3, WP6)

Before data can be collected or integrated, partners agree on:

  • sources, access rights, and sampling frames;
  • metadata standards (SDMX, DDI, DataCite);
  • ethical safeguards and GDPR-compliant procedures;
  • controlled vocabularies, authority files, and persistent identifiers.

These agreements are formalised in D1.2, D2.2, D3.2, and the Data Management Plan (D6.3). They ensure compliance with FAIR, OPA, and EU data-governance principles.

2.5.3 3. Software for data collection (WP4)

WP4 develops the open-source tools used to gather and ingest administrative data, survey data, platform usage data, and CMO records. These tools form the operational backbone of the pipeline. They include:

  • survey-data management scripts,
  • connectors for royalty and licensing accounts,
  • streaming API integration modules,
  • metadata templates for ingestion and harmonisation.

All tools adhere to the reproducibility and interoperability requirements defined in Annex 1 and the DMP.

2.5.4 4. Data acquisition (WP1, WP2, WP3)

Data are collected from:

  • collective management organisations (CMOs),
  • ministries and statistical offices,
  • cultural-heritage institutions,
  • surveys (enterprise and personal),
  • streaming-service APIs.

Each domain follows its own protocol (e.g. WP1 T1.2 sampling frames; WP3 T3.1 participation and wellbeing indicators). Data collected are documented in the DMP and cross-referenced with OPA-compliant folders.

2.5.5 5. Processing, enrichment, and harmonisation (WP4, WP5)

Raw inputs are processed using REPREX’s R-based openmusic-pipeline:

  • cleaning and pseudonymisation,
  • metadata harmonisation,
  • cross-linking with authority records,
  • structuring in SDMX/DataCite formats,
  • integration via persistent identifiers.

This step transforms heterogeneous inputs into consistent, analysis-ready datasets.

2.5.6 6. Validation for analysis and dissemination (WP4, WP5)

Before modelling can begin, WP4 and WP5 validate:

  • interoperability across sources,
  • semantic consistency,
  • statistical reproducibility,
  • versioning and provenance,
  • integration with the Open Music Observatory.

This ensures that indicators can be reproduced from source data and that all transformations are transparent.

2.5.7 7. Analysis and modelling (WP1–WP3)

The three thematic work packages conduct analyses based on their indicator sets:

  • WP1: music-sector economic valuation, satellite accounting extensions, export and employment metrics.
  • WP2: diversity, circulation, repertoire mapping, multilinguality.
  • WP3: participation, wellbeing, social impact, SDG alignment.

These analyses produce the evidence base for policy recommendations and are documented in open, executable notebooks.

2.5.8 8. Policy translation (WP5)

WP5 converts analytical results into Open Policy Analysis (OPA) documents — open, versioned, executable notebooks linking:

  • data,
  • code,
  • statistical results,
  • interpretative text.

Deliverables D5.6 and D5.7 demonstrate this approach. These “living policy documents” integrate directly with the Open Music Observatory and update as data refresh.

2.5.9 9. Dissemination and reuse (WP5)

Final datasets, indicators, and notebooks are published:

  • through the Open Music Observatory,
  • on Zenodo with DOIs,
  • and, where applicable, on the EU Open Data Portal.

This ensures transparency, auditability, and long-term reuse by policymakers, researchers, and cultural-sector stakeholders.

2.5.10 Summary

Taken together, these nine stages describe the way Open Music Europe operates: a unified, reproducible pipeline that transforms fragmented, multi-source data into validated, policy-ready evidence. The pipeline is the methodological backbone of the project and the operational logic of the Open Music Observatory.

2.6 Stakeholder Engagement and Early Feedback

Throughout the development of the Open Music Observatory, the consortium sought feedback from representative stakeholders across the music ecosystem, cultural-heritage institutions, data-infrastructure initiatives, and the open-knowledge community. Key presentations included:

  • Networkshop 2024, Eger, Hungary — possibilities of a cross-border federation between Slovak and Hungarian music data spaces (Antal 2024a).

  • IAMIC General Assembly and Conference 2024, Vienna — introduction of the Slovak Comprehensive Music Database and early Observatory concepts (Antal 2024c).

  • IAML Annual Conference 2025, Salzburg — presentation and poster on interoperability of music libraries and archives with public and private music services (Antal 2025a, 2025b).

  • Polifonia Stakeholder Session (2023) — metadata and interoperability workshop with performing-arts archives, national memory institutions, and academic partners.

  • Big Data Value Association / Gaia-X / Data Space Support Centre: Data Week 2024, Leuven — introduction of a European music dataspace and alignment with DSSC principles.

  • Wikimedia CEE Meeting 2024, Istanbul, and Wikimedia CEE Meeting 2025, Thessaloniki — technical presentations to Wikidata and Abstract Wikipedia communities (Antal 2024b).

CISAC European Committee Meeting as OpenMusE: Towards a Sustainable Licensing Market for AI Use of Protected Works in Vilnius, on 29 April 2025.

Our work was also presented at the CISAC European Committee Meeting as OpenMusE: Towards a Sustainable Licensing Market for AI Use of Protected Works in Vilnius, on 29 April 2025 (Mikš 2025) in comparison with similar metadata governance and repair initiatives from several countries.

  • Wikidata Conf 2025 (online),showing how our data model and governance can improve Wikidata itself.
    These consultations helped validate the Observatory’s technical, semantic, and governance foundations and informed its alignment with sectoral needs.

  1. See (European Commission 2021b, 2021a) on the policy-making process and objectives; Feasibility Study for the Establishment of a European Music Observatory (European Commission et al. 2020) and the Interoperable, Trustworthy, and Machine-Readable Copyright Data in the AI Era: Report of the CITF First Project (Partanen et al. 2025).↩︎

  2. Measuring and Reporting Regional Economic Value Added, National Income and Employment by the Music Industry in a Creative Industries Perspective. Memorandum of Understanding to Create a Regional Music Database to Support Professional National Reporting, Economic Valuation and a Regional Music Study (Artisjus et al. 2014) and Central And Eastern European Music Industry Report (2020) (Antal 2020).↩︎

  3. See (Senftleben et al. 2024); and (Antal 2025c), summarised in the internal document (Open Music Europe Consortium 2025).↩︎

  4. The Music ecosytem study: (Music Moves Europe 2024); the European Parliament’s resolution (European Parliament 2024) and our policy paper: (Antal 2025c).↩︎