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If (only) Data could speak... - Conference The sound of data - esch2022

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thu. 13 Oct.

15h30-18h30

The Sound of Data collective (an Esch2022 project) has partnered with Luxembourg's STATEC to organize a conference where experts and practitioners will discuss the challenges and opportunities around innovation in data modeling and popularization, data journalism and data-driven communication. And in that context, consider what data sonification and data visualization can bring to the table.

️Keynote speakers Duncan Geere and Miriam Quick will begin the event with a presentation titled A Sonic Vocabulary: Turning Data into Sound And Music with Loud Numbers. The presentation will be followed by a panel discussion and a Q&A session with the audience.

- Duncan Geere is an information designer based in Helsingborg, Sweden with an interest in climate and the environment. He strives to communicate complex and nuanced information to a wider audience for clients such as Information is Beautiful, The Gates Foundation and Project Drawdown. He currently works part-time for the climate charity Possible, and he is also a generative artist and musician.

- Miriam Quick is a data journalist, researcher and author who explores new ways to communicate data. She has written data stories for the BBC, worked as a researcher for Information is Beautiful and the New York Times, and co-created works of art that represent data through images, sculpture and sound. His first book, I am a book. I am a portal to the universe, co-authored with Stefanie Posavec, won the 2021 Royal Society Young People's Book Prize.

- Duncan Geere and Miriam Quick are the founders of The Loud Numbers data sonification studio, and hosts of The Loud Numbers podcast.

Round table participants: Tom Haas (Head of Unit, STATEC), Emma Schymanski (PI, Environmental Cheminformatics, Luxembourg Center for Systems Biomedicine), Miriam Quick (Data Journalist, Researcher, Author), Jamie Perera (Composer, Producer, Sound Artist) , Lara Schwenner (science journalist, quarks/wdr).