Sonification and sound design for astronomy research, education and public engagement

Zanella, Anita; Harrison, C. M.; Lenzi, Sara; Cooke, Jeff; Damsma, P.; Fleming, Scott W.

doi:10.1038/s41550-022-01721-z

Cited by 27 publications

(27 citation statements)

References 29 publications

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“…Alternatively, sound could be used as an additional data dimension, as the human auditory sense is excellent in detecting structure or symmetries in (periodic) time-dependent data. This opportunity has been explored in high-energy physics 53 and in dozens of projects in astronomy 54 . A powerful algorithm might be able to identify symmetries in the underlying data and project them into 3D video with sound, which might help the human to recognize and subsequently understand new properties within the data generated by the computational microscope.…”

Section: Three Dimensions Of Computer-assisted Understandingmentioning

confidence: 99%

On scientific understanding with artificial intelligence

et al. 2022

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An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology. However, scientists would not be entirely satisfied because they would want to comprehend how the oracle made these predictions. This is scientific understanding, one of the main aims of science. With the increase in the available computational power and advances in artificial intelligence, a natural question arises: how can advanced computational systems, and specifically artificial intelligence, contribute to new scientific understanding or gain it autonomously? Trying to answer this question, we adopted a definition of ‘scientific understanding’ from the philosophy of science that enabled us to overview the scattered literature on the topic and, combined with dozens of anecdotes from scientists, map out three dimensions of computer-assisted scientific understanding. For each dimension, we review the existing state of the art and discuss future developments. We hope that this Perspective will inspire and focus research directions in this multidisciplinary emerging field.

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Section: Three Dimensions Of Computer-assisted Understandingmentioning

confidence: 99%

On scientific understanding with artificial intelligence

et al. 2022

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“…The experts in astronomy broadly described the specific nature of astronomical data (light curve, spectrum, image, time series, etc. ), together with some of the main astronomy-focused sonification tools that are already currently used by researchers in that domain 2 2 . Detailed information about five of these tools was presented:…”

Section: Context Of the Perspective 11 A Participatory Workhop As Res...mentioning

confidence: 99%

Sound experts’ perspectives on astronomy sonification projects

et al. 2022

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The Audible Universe project aims at making dialogue between two scientific domains investigating two distinct research objects, briefly said, Stars and Sound. It has been instantiated within a collaborative workshop that started to mutually acculturate both communities, by sharing and transmitting respective knowledge, skills and practices. One main outcome of this exchange was a global view on the astronomical data sonification paradigm that allowed to observe either the diversity of tools, uses and users (including visually-impaired people), but also the current limitations and potential ways of improvement. From this perspective, the current paper presents basic elements gathered and contextualised by sound experts in their respective fields (sound perception / cognition, sound design, psychoacoustics, experimental psychology), in order to anchor sonification for astronomy in a more well-informed, methodological and creative process.

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“…In musical contexts, data can map to these sonic dimensions, as well as higher-order musical dimensions, such as tempo, form, and timbre” (Sawe et al, 2020 ). A recent review study on sonification strategies in astronomical research (Zanella et al, 2022 ) highlights the added value of using sound to increase the accessibility of scientific knowledge, especially for the engagement of a visually impaired non-expert audience. In a meta-study, Dubus and Bresin ( 2013 ) charted strategies for the sonification of real-world physical processes.…”

Section: Introductionmentioning

confidence: 99%

Climate data sonification and visualization: An analysis of topics, aesthetics, and characteristics in 32 recent projects

2023

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IntroductionIt has proven a hard challenge to stimulate climate action with climate data. While scientists communicate through words, numbers, and diagrams, artists use movement, images, and sound. Sonification, the translation of data into sound, and visualization, offer techniques for representing climate data with often innovative and exciting results. The concept of sonification was initially defined in terms of engineering, and while this view remains dominant, researchers increasingly make use of knowledge from electroacoustic music (EAM) to make sonifications more convincing.MethodsThe Aesthetic Perspective Space (APS) is a two-dimensional model that bridges utilitarian-oriented sonification and music. We started with a review of 395 sonification projects, from which a corpus of 32 that target climate change was chosen; a subset of 18 also integrate visualization of the data. To clarify relationships with climate data sources, we determined topics and subtopics in a hierarchical classification. Media duration and lexical diversity in descriptions were determined. We developed a protocol to span the APS dimensions, Intentionality and Indexicality, and evaluated its circumplexity.ResultsWe constructed 25 scales to cover a range of qualitative characteristics applicable to sonification and sonification-visualization projects, and through exploratory factor analysis, identified five essential aspects of the project descriptions, labeled Action, Technical, Context, Perspective, and Visualization. Through linear regression modeling, we investigated the prediction of aesthetic perspective from essential aspects, media duration, and lexical diversity. Significant regressions across the corpus were identified for Perspective (ß = 0.41***) and lexical diversity (ß = −0.23*) on Intentionality, and for Perspective (ß = 0.36***) and Duration (logarithmic; ß = −0.25*) on Indexicality.DiscussionWe discuss how these relationships play out in specific projects, also within the corpus subset that integrated data visualization, as well as broader implications of aesthetics on design techniques for multimodal representations aimed at conveying scientific data. Our approach is informed by the ongoing discussion in sound design and auditory perception research communities on the relationship between sonification and EAM. Through its analysis of topics, qualitative characteristics, and aesthetics across a range of projects, our study contributes to the development of empirically founded design techniques, applicable to climate science communication and other fields.

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Sonification and sound design for astronomy research, education and public engagement

Cited by 27 publications

References 29 publications

On scientific understanding with artificial intelligence

On scientific understanding with artificial intelligence

Sound experts’ perspectives on astronomy sonification projects

Climate data sonification and visualization: An analysis of topics, aesthetics, and characteristics in 32 recent projects

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