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气候数据的听觉化与可视化:对近期32个项目的主题、美学及特征的分析

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

作者信息

Lindborg PerMagnus, Lenzi Sara, Chen Manni

机构信息

SoundLab, School of Creative Media, City University of Hong Kong, Kowloon, Hong Kong SAR, China.

Critical Alarms Laboratory, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands.

出版信息

Front Psychol. 2023 Jan 25;13:1020102. doi: 10.3389/fpsyg.2022.1020102. eCollection 2022.

Abstract

INTRODUCTION

It 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.

METHODS

The 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.

RESULTS

We 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.

DISCUSSION

We 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.

摘要

引言

事实证明,利用气候数据来推动气候行动是一项艰巨的挑战。科学家通过文字、数字和图表进行交流,而艺术家则运用动作、图像和声音。数据声音化,即将数据转化为声音,以及可视化,提供了用往往具有创新性和令人兴奋的结果来呈现气候数据的技术。数据声音化的概念最初是从工程学角度定义的,虽然这种观点仍然占据主导地位,但研究人员越来越多地利用电子声学音乐(EAM)的知识,以使声音化更具说服力。

方法

审美视角空间(APS)是一个二维模型,它架起了以实用为导向的数据声音化与音乐之间的桥梁。我们首先回顾了395个数据声音化项目,从中选取了32个针对气候变化的项目组成语料库;其中18个项目的子集还整合了数据可视化。为了厘清与气候数据源的关系,我们在分层分类中确定了主题和子主题。确定了描述中的媒体时长和词汇多样性。我们制定了一个跨越APS维度(意向性和索引性)的方案,并评估了其环形性。

结果

我们构建了25个量表,以涵盖一系列适用于数据声音化和数据声音化 - 可视化项目的定性特征,并通过探索性因素分析,确定了项目描述的五个基本方面,分别标记为行动、技术、背景、视角和可视化。通过线性回归建模,我们研究了从基本方面、媒体时长和词汇多样性对审美视角的预测。在整个语料库中,确定了视角(ß = 0.41)和词汇多样性(ß = -0.23)对意向性的显著回归,以及视角(ß = 0.36)和时长(对数;ß = -0.25)对索引性的显著回归。

讨论

我们讨论了这些关系在特定项目中是如何体现的,也包括在整合了数据可视化的语料库子集中的体现,以及美学对旨在传达科学数据的多模态表示设计技术的更广泛影响。我们的方法受到声音设计和听觉感知研究社区中关于数据声音化与电子声学音乐关系的持续讨论的启发。通过对一系列项目的主题、定性特征和美学进行分析,我们的研究有助于开发基于实证的设计技术,适用于气候科学传播及其他领域。

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