Data-to-music sonification and user engagement

Jonathan Middleton; Jaakko Hakulinen; Katariina Tiitinen; Juho Hella; Tuuli Keskinen; Pertti Huuskonen; Jeffrey Culver; Juhani Linna; Markku Turunen; Mounia Ziat; others; Roope Raisamo

doi:10.3389/fdata.2023.1206081

Data-to-music sonification and user engagement

Jonathan Middleton
, Jaakko Hakulinen
, Katariina Tiitinen
, Juho Hella
, Tuuli Keskinen
, Pertti Huuskonen
, Jeffrey Culver
, Juhani Linna
, Markku Turunen
, Mounia Ziat
, others
, Roope Raisamo

Experience Design

Research output: Contribution to journal › Article

Abstract

The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, called data-to-music sonification, reveals how musical characteristics can serve analytical purposes with enhanced user engagement. An existing user engagement scale has been applied to measure engagement levels in three conditions within melodic, rhythmic, and chordal contexts. This article reports findings from a user engagement study with musical traits and states the benefits and challenges of using musical characteristics in sonifications. The results can guide the design of future sonifications of multivariable data.

Original language	English
Journal	Frontiers in big Data
Volume	6
Issue number	Issue
DOIs	https://doi.org/10.3389/fdata.2023.1206081
State	Published - 2023

Access to Document

10.3389/fdata.2023.1206081

Cite this

@article{2a278fbf2c9844df9652bbf36ea73825,

title = "Data-to-music sonification and user engagement",

abstract = "The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, called data-to-music sonification, reveals how musical characteristics can serve analytical purposes with enhanced user engagement. An existing user engagement scale has been applied to measure engagement levels in three conditions within melodic, rhythmic, and chordal contexts. This article reports findings from a user engagement study with musical traits and states the benefits and challenges of using musical characteristics in sonifications. The results can guide the design of future sonifications of multivariable data.",

author = "Jonathan Middleton and Jaakko Hakulinen and Katariina Tiitinen and Juho Hella and Tuuli Keskinen and Pertti Huuskonen and Jeffrey Culver and Juhani Linna and Markku Turunen and Mounia Ziat and others and Roope Raisamo",

year = "2023",

doi = "10.3389/fdata.2023.1206081",

language = "English",

volume = "6",

journal = "Frontiers in big Data",

number = "Issue",

}

TY - JOUR

T1 - Data-to-music sonification and user engagement

AU - Middleton, Jonathan

AU - Hakulinen, Jaakko

AU - Tiitinen, Katariina

AU - Hella, Juho

AU - Keskinen, Tuuli

AU - Huuskonen, Pertti

AU - Culver, Jeffrey

AU - Linna, Juhani

AU - Turunen, Markku

AU - Ziat, Mounia

AU - others, null

AU - Raisamo, Roope

PY - 2023

Y1 - 2023

N2 - The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, called data-to-music sonification, reveals how musical characteristics can serve analytical purposes with enhanced user engagement. An existing user engagement scale has been applied to measure engagement levels in three conditions within melodic, rhythmic, and chordal contexts. This article reports findings from a user engagement study with musical traits and states the benefits and challenges of using musical characteristics in sonifications. The results can guide the design of future sonifications of multivariable data.

AB - The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, called data-to-music sonification, reveals how musical characteristics can serve analytical purposes with enhanced user engagement. An existing user engagement scale has been applied to measure engagement levels in three conditions within melodic, rhythmic, and chordal contexts. This article reports findings from a user engagement study with musical traits and states the benefits and challenges of using musical characteristics in sonifications. The results can guide the design of future sonifications of multivariable data.

UR - https://dx.doi.org/10.3389/fdata.2023.1206081

U2 - 10.3389/fdata.2023.1206081

DO - 10.3389/fdata.2023.1206081

M3 - Article

VL - 6

JO - Frontiers in big Data

JF - Frontiers in big Data

IS - Issue

ER -

Data-to-music sonification and user engagement

Abstract

Access to Document

Other files and links

Fingerprint

Cite this