Appendix
CEEMID is a data integration system that could provide to be a model and starting point of building a European Music Observatory based on open data, open-source software using open collaboration with the music industry, statisticans and academia, using best statistics, data science and AI practices. CEEMID has created thousands of high-value, hard music industry indicators using open data sources, industry data sources, surveys and various APIs to relevant other data sources.
CEEMID is aiming to transfer thousands of indicators and a verifiable, open-source software that creates them to the European Music Observatory to give Europe-wide acces timely, reliable, actionable statistics and indicators for the music industry, policymakers and music professionals. (Read more about our data coverage and geographical coverage).
We hope that this report demonstrated that CEEMID is capable of producing high-quality indicators for analysis and AI for the innovation pillar of the European Music Observatory by creating input data on the Music Economy of Europe, Music Diversity and Circulation and on Music, Society & Citizenship.
We did not include a detailed data reference list in the main text, but upon request from the authors of the Feasibility Study on the European Music Observatory, we created a Documentation Wiki Page and listed the data references with some notes on data handling in the technical notes on Central European Music Industry Report 2020 and updated the bibliography18. For further details, please contact CEEMID.
Historically CEEMID started out as the Central and Eastern European Music Industry Databases out of necessity following a CISAC Good Governance Seminar for European Societies in 2013. The adoption of European single market and copyright rules, and the increased activity of competition authority and regulators required a more structured approach to set collective royalty and compensations tariffs in a region that was regarded traditionally as data-poor with lower quantitiy of industry and government data sources available. In 2014 three collective management societies, Artisjus, HDS and SOZA, realized the need to make further efforts to modernize the way they measure their own economic impact and the economic value of their licenses in order to remain competitive in advocating their interests vis-à-vis domestic governments, international organizations like CISAC and GESAC and the European Union. They signed a Memorandum of Understanding Measuring and Reporting Regional Economic Value Added, National Income and Employment by the Music Industry in a Creative Industries Perspective with their consultant to set up the CEEMID databases and to harmonize their efforts.19
CEEMID cooperated over five years with almost 100 music organizations, and thousands of music professionals participated in our surveys and workshops. We would like to thank them for their support and their views here.
In no particular order, the author would like to thank Nenad Marčec, Anton Popovič, András Szinger for their initial support in initiating CEEMID; long-term users of our data, Ľubomír Burgr, Adam Dvořák, Marina Feric Jančic, Péter Horváth, Eszter Kabai, Dávid Kitzinger, Tereza Landová, Tomáš Mikš, Darko Stanicic, Péter Benjamin Tóth; in ex ante grant evaluations, Zsolt Bajnai, Márton Náray and Zsófi Sápi; great educators Emília Barna and Fruzsina Morcz; in music exports, Dávid Bali, the Hangfoglaló, the Lala, the Music Estonia and the SoundCzech teams, our partners in national surveys Dávid Bali, Agnė Begetė, Lilyt Bleyan, Gergely Békés, Tanja Bukvic, Santa Cristescu, Richárd Demčák, Stefan Germanov, Mark Adam Harold, Franz Hergovich, Viljem Marjan Hribar, Zsolt Jeszenszky, Nikola Jovanovic, Kristina Delfin Kanceljak, Rumyana Koleva, Sandra Laura Luhtein, Dan Murau, Martin Nedvěd, Slobodan Nešović, Anton Petrov, Darjo Rot, Virgo Sillamaa, the Consolidated Independent data team Theo Gardner, Andy McFarland and Jerome Wynne; Tamás Falus and Péter Molnár at the Kantar-Hoffmann survey team; workshop assistants Kati Csatlós, Brenda Dobrovicsova, Zsuzsa Fried, Monika Klementová, research assistant Kátya Nagy, cover designer Aistė Zabitaitė; the consultants of European Music Observatory Marin Martin Clarke, Emmanuel Legrande, Fabien Miclet, Paul Vroonhof. Special thanks for their ideas and criticism to Tereza Raabová and Sanne de Rover.
This report was created in a reproducible research framework with bookdown (Xie 2020), using the datasets of CEEMID. The visualizations were made with ggplot and ggalluvial (Wickham et al. 2019; Wickham 2016; Brunson 2019). Whenever European data was charted, we used the ©EuroGeographics administrative boundary visualizations published by Eurostat.
References
Brunson, Jason Cory. 2019. ggalluvial: Alluvial Plots in ’ggplot2’. https://CRAN.R-project.org/package=ggalluvial.
Wickham, Hadley. 2016. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.
Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, and Hiroaki Yutani. 2019. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics.
Xie, Yihui. 2020. bookdown: Authoring Books and Technical Documents with R Markdown. https://CRAN.R-project.org/package=bookdown.