Pillars | CCSI Data Observatory

Creative Economy

Thu, 06 Oct 2022 14:40:00 +0200

In the case of Pillar 1 – Music & Economy, we are usually able to locate the source of the data, and we have some experience in processing the data and bringing it to light. We have mapped many perceived data gaps to the various data harmonization projects of GESAC and CISAC, and we will seek cooperation with these organizations and their members to find a secure and voluntary way to retrieve the data.

Within the OpenMuse project, we will demonstrate the capacity of improved data to increase artist revenues within a short- to medium-term timeframe. This pilot project will directly build upon results of CEEMID and other prior projects undertaken by Artisjus, SOZA, and Reprex. The partners will replicate a full market model used to measure the use of recorded music in Hungary and Slovakia. Artisjus and SOZA will revise and validate this full market model using fully standardised data, collected and harmonised via the OpenMusE music data software ecosystem.

By bringing the model into line with the standards of Open Policy Analysis, open science, and open-source software development, the consortium will enable its transfer to the Bulgarian market with partner Musicautor. In all three countries, the Consortium will generate replicable, detailed “live policy documents” including gross value added, employment, and other important economic variables which will be integrated into a precise valuation of all uses of recorded music within the national context. These valuations will depend on standardised data from GESAC, CISAC, and potentially from IFPI, Aepo-Artis, and SCAPR, and provided via partners Artisjus, SOZA, and MUSICAUTOR. Because the “live policy documents” will be generated semi-automatically using the software ecosystem introduced above, similar documents could be created nearly instantly for any GESAC/CISAC/IFPI national member organisation that provided comparable data on recorded music within their national context. The OpenMusE Report on the European Music Economy will be published as a “live policy document” including the Bulgarian, Hungarian, and Slovakian valuations, as well as valuations for any national market in which a representative organisation consents to provide data.

In other cases, we will rely on on the 2019/1024/EU Open Data Directive to access, process, document, and disseminate the data.

The music.dataobservatory.eu monitors the music markets with an economic methodology: we not only measure market volumes and prices, but we also measure both demand- and supply side indicators so that we can forecast future market volumes or prices. (See Innovation pillar — 4.2 Forecasting)

Music is not a purely market activity. Music and music services have consumers who pay for it one way or another, but there are non-market forms of music (for example, in liturgy) and music markets are overshadowed by a very large illegal market. Therefore, instead of “music consumption” we use the more appropriate statistical terms of access and participation. we do measure non-market form,s but currently we do not address teh data gap the “impact of the non-profit sector”.

Pillar 1 - Music Economy
Topic	Description
pillar	problem	availability	feasibility
Pillar 1	Value of music sector	One-off	EY study on the cultural and creative industries (2015)
Pillar 1	Value of music sector	One-off or one recast	CEEMID studies on national music economies
Pillar 1	Employment	One-off	EY study on the cultural and creative industries (2015)
Pillar 1	Employment	One-off or one recast	CEEMID national music industry reports
Pillar 1	Employment	Annual	Eurostat, lacking granularity
Pillar 1	Employment	Data gap	Absence of granularity on the employment of the various sub-sectors, in particular in defining the roles of the various sub-sectors and the importance of the not-for-profit sector in terms of employment.
Pillar 1	Employment	Data gap	HU, SK pilot successful to add granularity.
Pillar 1	Value of music sector	Data gap	No EU-level assessment since 2015
Pillar 1	Strucutre of the market	Data gap	Absence of pan-European data detailing the number of companies, employees, revenues for the sector and the subsectors.
Pillar 1	The impact of the not-forprofit sector on the overall economy of the music sector	Data gap	No data available on the specific impact of the not-for-profit sector, especially in the live music sub-sector
Pillar 1	Recorded music	Subject to partnership with IFPI	IFPI
Pillar 1	Authors and publisher’s stream	CISAC partnership	CISAC
Pillar 1	Authors and publisher’s stream	GESAC	GESAC
Pillar 1	Recorded music stream - performer rights	Data gap	No aggregated data on neighbouring rights collections Partner with AEPO-ARTIS and SCAP.
Pillar 1	Music publishing	Data gap	No aggregated data on the music European music publishing business
Pillar 1	Synchronisation rights	Data gap	IFPI data available on the recorded music side but not on the publishing side.
Pillar 1	Independent music companies	Data gap	No aggregated data on the independent music sector (value, number of companies, employees, etc.)
Pillar 1	Live music	Data gap	Some data is compiled by Live DMA, ETEP or Yourope, but there is no aggregated data on the pan-European live music sector listing the value of the market, the number and size of venues and shows, number of festivals, share of European artists, among other data points.
Pillar 1	Exports	Data gap	No pan-European data on the export flows between EU countries and outside the EU.
Pillar 1	Exports	Data gap	Embedded cultural tourism export.
Pillar 1	Music retail	Data gap	Granular data on some countries via retail associations (UK, France, Germany) but no pan-European aggregated data.
Pillar 1	Financing of the music sector	Data gap	No aggregated data on how the sector is financed (from investment fund to bank loans and subsidies).
Pillar 1	Live music regulation	Data gap	No aggregated information available on the various legal and tax systems within the EU applied to the live music sector.
Pillar 1	Copyright regulations and evolution of copyright regimes	Data gap	Although many copyright laws applicable in Europe originate from the Commission, there are few instruments available to monitor the state of copyright regulation across the EU

Art+Tech

Thu, 06 Oct 2022 08:12:00 +0200

We will connect to several innovation topics in music by providing research, data, and evidence. Building on the work of the Blockchain & Society research project of our Consortium member, the Institute for Information Law IViR at the University of Amsterdam, we will address issues related to NFT and blockchain technologies in music.
Connecting to the work of various music stakeholders in Finland, we will experiment with the safe data sharing of confidential data, avoiding the extreme pitfalls of ‘radical openness’ and ‘closed data’. With the University of Bologna, and eight years of experience in sensitive data sharing with the Digital Music Observatory (formerly: CEEMID), we will create various statistical methods to create anonymized and synthetic datasets that do not endanger business or private data.
We are going to design indicators and carry out a landscape mapping with Music Tech Europe, a new organization that aims to become the representative of music startups and music ecosystems in the European Union.


Topic	Description
pillar	problem	availability	feasibility
Pillar 4	Several reports cover the evolution of music and tec	Available	Music Ally, Midia Research…
Pillar 4	Blockchain and music	Data gap	No authoritative assessment of the impact of Blockchain on the music sector and of the EU-powered initiatives linking Blockchain and music.
Pillar 4	Artificial intelligence, machine learning and music	Data gap	No authoritative assessment of the impact of AI and machine learning on the music sector and of the EUpowered initiatives linking AI and music.
Pillar 4	Future of streaming	Data gap	No authoritative assessment of the future development of streaming and its impact on the EU music sector
Pillar 4	Digital revenues in the music sector and the relevant business models	Data gap	In the UK the report ‘Dissecting the digital dollar’ commission by the MMF to CMU, but no similar European study.
Pillar 4	Mapping the flow of digital revenues in the music sector and the relevant business models in Europe	Data gap	Digital distribution of music has introduced new complex business models that are not always transparent.
Pillar 4	Music start-ups in the EU	Data gap	No authoritative mapping of start-ups involved in music at EU level.
Pillar 4	The impact of artists’ ‘do it yourself’ culture on the economy of the sector	Data gap	Although more artists are going to market with their music without the traditional support of labels, there is no overview of how deep the trend is, how it affects the music ecosystem or what policy frameworks can or should support such activity.
Pillar 4	Funding mechanisms for music	Data gap	No regular overview of the funding schemes in Europe relevant to the music business.

Cultural Diversity & Circulation

Thu, 06 Oct 2022 08:12:00 +0200

WP2 Music diversity and circulation will culminate in a pilot project conducted in Slovakia, Lithuania, and Ukraine by SOZA, MXF, and MEU.

The WP2 pilot project will demonstrate the feasibility of increasing local artist representation in radio and streaming, via trustworthy AI and evidence-based regulatory policy. In the “Listen Local” project, partners SOZA and Reprex created the Slovak Demo Music Database (SDMDb) as a reference database to measure the market share of Slovak music in radio and streaming, and created a prototype of a recommendation system that meets trustworthy AI criteria and is able to achieve similar cultural diversity goals as laid out by Slovak media legislation in 2015: i.e., to achieve 15% “Slovak” market share in radio playlists.

Culture And Society

Thu, 06 Oct 2022 08:12:00 +0200

In the OpenMuse WP3 Music, society, and citizenship will culminate in a pilot project conducted in Italy by MIH. The WP3 pilot project will demonstrate the ability of reproducible research and innovation tools to help MSMEs comply with emerging social and environmental sustainability regulations, at a viable cost. Within the pilot project, MIH will utilise the OpenMuse open music data software ecosystem to create an environmental impact report – as will soon be required of many European MSMEs. For this, we will add new functionality to software that was originally developed for economic and environmental impact assessments for the Hungarian and Slovak Music Industry Reports. In addition, more detailed social and governance reporting will be carried out with MIH. As founders of the Keychange program for gender equality in music, MIH is dedicated to transferable piloting on environmental sustainability (covering greenhouse gas and water use at a minimum), social sustainability (focusing on the gender pay gap), and governance sustainability (focusing on live performance kickbacks and recorded performance payola schemes as corruption risks in the music industry).

The environmental, social, and governance sustainability data collection will be piloted in Italy and transferred within the project lifespan to Bulgaria. As in the WP1 and WP2 pilot projects, the methods and software utilised will be fully open source, and thus open to, and replicable by, any national stakeholders who can collect the inputs required.

Open Policy Analysis

Sun, 06 Feb 2022 14:00:00 +0000

Our ambition is to truly maximize transparency, (re)usability, scientific, policy, and business impact while embracing the best practices laid out in the the recommendations of the Reproducibility of scientific results scoping report, and the Progress on Open Science: Towards a Shared Research Knowledge System policy documents of the European Commission’s DG Research & Innovation, as well as the best practices outlined in the evidence-based Knowledge4Policy K4P platform of the European Commission. For the first time in Europe, we will apply and contextualize the Open Policy Analysis Guidelines, which grew out of several initiatives in research transparency with the aim of maximizing benefits in the context of the Foundations for Evidence-based Policy Making Act of 2018 initiative in the United States. We want to ensure that by relying not only on the best European practices, but considering trans-Atlantic experiences, we will make the most out of the opportunities offered by the European Open Data Directive of 2019. This will not only mean rendering a dramatically increased data availability for our partners, as well as increased quality assurance and transparency in our work, but also immediate data access. Following the EU & US best practices we have already placed before sumbitting our proposal our important software tools, methodologies, and sample data in the Zenodo repository.

Our new software will continue to run in the cloud, depositing all of our findings—Findable, Accessible, Interoperable and Reuseable digital assets, including our well-designed and user-tested indicators in 41 data gap fields—into our Digital Music Observatory, which already hosts a modern REST API similar to the Eurostat Rest API. We are still adjusting this service in order to find a way to best implement SDMx and other data standards while maintaining ease of use. We anticipate enhanced usability by April 2022.

Layer	Goal	Target	Example
Open Output	Ensure unified output	We comply with the level 3 requirements and we will create a showcase how to do this best following EU open science recommendations.	See our example.
Open Output	Establish a clear link between input and output	We will produce more than 100 outputs, some only as indicators, and others in form of policy analysis, we will comply with level 1,2,3 as necessary.	Our affiliated music industry partners will create cases studies with interactive tools (level 3). See our Slovak case study which came with a Shiny App that analyzed music recommendations.
Open Analysis	Provide clear accounts of all methodological procedures in a way that is easily interpreted by an informed reader.	We accomplish level 3 with placing the code in clearly documented. into a dynamic document, or open notebook	See for example our blogpost on automatic forecasting for the music industry.
Open Analysis	Share raw (or analytic) data and materials in a way that the analysis is reproducible with minimal effort.	We will accomplish level 3 through trusted repositories following EU recommendations. We will use the Zenodo repository developed by CERN and the EU’s OpenAIRE project.	See our solution on Zenodo.
Open Analysis	Share an open report that includes clear accounts of all methodological procedures, data, and assumptions.	We would like to go beyond the level 3 requirements of the OPA with using standardized documentation languages, such as SDMX statistical metadata and its standardized codebooks, and comply with both Dublin Core and DataCite extended, recommended standarized reporing.	See our example An Empirical Analysis of Music Streaming Revenues and Their Distribution created for the UK Intellectual Property Office’s evidence-based policy effort in music streaming.
Open Materials	Standardize the file structure so that materials are organized in a way that is accessible to an informed reader.	We comply with the level 3 requirements. Our versioned controled output is on Github.	See an example on Github.
Open Materials	Label and document each input, including data, research, and guesswork.	We will go beyond level 3 requirements, because we want to make sure that our labelling and documentation is interopreable, and we apply various metadata standards for this purpose.	See our example explaining how we document our datasets in our API.
Open Materials	Ensure that code/spreadsheets are reproducible.	All our spreadsheets are machine generated for the convenience of the user who uses spreadsheet applications, but everything can be run with a click, which accomplishes level 3, and maintains the convenience of level 1-2 for the user. We go further with creating authoritative copies of each dataset and visualization with DOIs. We also produce an API which gives programatic or single table access to both the data and standardized codebooks.	See our API. All our datasets are described in detail on Zenodo and Figshare, too.
Open Materials	Use a version control strategy.	We use Git version control, and we employ various repositories and project documentation tools on Github. These are linked with the Zenodo EU open repository and our data API.	See our example intergration.