The Design of Data Sonification
Towards shared methods and tools
We are very glad to invite you to the Sound and Music Interaction Seminar with Sara Lenzi.
Tid: Ti 2023-05-30 kl 15.00
Videolänk: Zoom link
Medverkande: Sara Lenzi, Delft University of Technology
In a data-intense society, sonification is gaining momentum as an alternative or complement to data visualization. Nonetheless, a series of unresolved issues are still preventing sonification’s full transition from a niche scientific method into a widely adopted medium that could impact the way people make sense of complex phenomena. The lack of shared design tools and methods, common in other design-related disciplines, is among the most cited obstacles. Starting from the Data Sonification Archive (https://sonification.design), an online collection of more than 400 projects, we will map the world of sonification and understand who uses it, why, and for whom. We will navigate through a Sonification Design Space that informed the definition of the Data Sonification Canvas, a design tool to support authors (designers, composers, researchers) to integrate sound into data experiences. The canvas has been recently evaluated by a pool of 20 users. Results from the evaluation study and plans for future iterations of the canvas will be shared.
Sara Lenzi is a postdoctoral researcher at the Critical Alarms Lab, Faculty of Industrial Design Engineering, TU Delft. She holds a Ph.D. in Design from Politecnico di Milano. Trained as a Western classical music performer and electroacoustic composer, she has a background in philosophy and STS studies (Science and Technology in Society). After a decade spent as a sound branding consultant for international brands (among others Ducati Motors, Singapore Changi Airport, BMW Asia, Citibank), she now dedicates full-time to research. Co-founder of the Data Sonification Archive, her main research area is sonification for AI-based anomaly detection in digital-physical networks. She is particularly interested in how sound and sonification can facilitate human-AI communication and support the decision-making process.