Niklas Rönnberg

dblp:177/4799 · DBLP profile ↗
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7ranked-venue papers
2as first author
5since 2021 · last 2026
0000-0002-1334-0624ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 6 · 2 first-author · 4 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 since 2021
YearPublicationVenuePosition
2026 Evaluation of Advanced Multimodal Interfaces: Towards New Methodologies
abstract
This workshop brings together researchers in visualization, sonification, and HCI to advance methods for evaluating integrated audiovisual representations. Recognizing that meaning emerged through cross‑modal interaction rather than isolated channels, participants explored frameworks for assessing coherence, accessibility, sensemaking, and user experience. The workshop will identify methodological gaps, share emerging practices, and foster collaboration toward more rigorous, inclusive, and reproducible evaluation of multimodal systems.
Niklas Rönnberg, Camilla Forsell
AVI1
2024 Open Your Ears and Take a Look: A State-of-the-Art Report on the Integration of Sonification and Visualization
abstract
Abstract The research communities studying visualization and sonification for data display and analysis share exceptionally similar goals, essentially making data of any kind interpretable to humans. One community does so by using visual representations of data, and the other community employs auditory (non‐speech) representations of data. While the two communities have a lot in common, they developed mostly in parallel over the course of the last few decades. With this STAR, we discuss a collection of work that bridges the borders of the two communities, hence a collection of work that aims to integrate the two techniques into one form of audiovisual display, which we argue to be “more than the sum of the two.” We introduce and motivate a classification system applicable to such audiovisual displays and categorize a corpus of 57 academic publications that appeared between 2011 and 2023 in categories such as reading level, dataset type, or evaluation system, to mention a few. The corpus also enables a meta‐analysis of the field, including regularly occurring design patterns such as type of visualization and sonification techniques, or the use of visual and auditory channels, showing an overall diverse field with different designs. An analysis of a co‐author network of the field shows individual teams without many interconnections. The body of work covered in this STAR also relates to three adjacent topics: audiovisual monitoring, accessibility, and audiovisual data art. These three topics are discussed individually in addition to the systematically conducted part of this research. The findings of this report may be used by researchers from both fields to understand the potentials and challenges of such integrated designs while hopefully inspiring them to collaborate with experts from the respective other field.
Kajetan Enge, Elias Elmquist, Valentina Caiola, Niklas Rönnberg, Alexander Rind, Michael Iber, Sara Lenzi, Fangfei Lan, Robert Höldrich, Wolfgang Aigner
Comput. Graph. Forum4
2024 Parallel Chords: an audio-visual analytics design for parallel coordinates
abstract
Abstract One of the commonly used visualization techniques for multivariate data is the parallel coordinates plot. It provides users with a visual overview of multivariate data and the possibility to interactively explore it. While pattern recognition is a strength of the human visual system, it is also a strength of the auditory system. Inspired by the integration of the visual and auditory perception in everyday life, we introduce an audio-visual analytics design named Parallel Chords combining both visual and auditory displays. Parallel Chords lets users explore multivariate data using both visualization and sonification through the interaction with the axes of a parallel coordinates plot. To illustrate the potential of the design, we present (1) prototypical data patterns where the sonification helps with the identification of correlations, clusters, and outliers, (2) a usage scenario showing the sonification of data from non-adjacent axes, and (3) a controlled experiment on the sensitivity thresholds of participants when distinguishing the strength of correlations. During this controlled experiment, 35 participants used three different display types, the visualization, the sonification, and the combination of these, to identify the strongest out of three correlations. The results show that all three display types enabled the participants to identify the strongest correlation — with visualization resulting in the best sensitivity. The sonification resulted in sensitivities that were independent from the type of displayed correlation, and the combination resulted in increased enjoyability during usage.
Elias Elmquist, Kajetan Enge, Alexander Rind, Carlo Navarra, Robert Höldrich, Michael Iber, Alexander Bock 0002, Anders Ynnerman, Wolfgang Aigner, Niklas Rönnberg
Pers. Ubiquitous Comput.10
2024 What you hear is what you see? Perspectives on modalities in sound and music interaction
Michael Iber, Kajetan Enge, Niklas Rönnberg, Annika Neidhardt, Norbert Schnell, Katharina Pollack, Maria Kallionpää, Alan Chamberlain
Pers. Ubiquitous Comput.3
2022 Workshop on Audio-Visual Analytics
abstract
In their daily lives, people use more than one sense to perceive and interpret their environment. Likewise, audio-visual interfaces can support human data analysts better than interfaces relying on just one sense. While the research communities of sonification and visualization have both carried out extensive research on the auditory and visual representation of data, comparatively little is known about their systematic and complementary combination for data analysis. After two workshops at Audio Mostly 2021 and IEEE VIS, this 3rd workshop on audio-visual analytics continues building a community of researchers interested in combining visualization and sonification.
Wolfgang Aigner, Kajetan Enge, Michael Iber, Alexander Rind, Niklas Elmqvist, Robert Höldrich, Niklas Rönnberg, Bruce N. Walker
AVI7
2019 A Study on 2D and 3D Parallel Coordinates for Pattern Identification in Temporal Multivariate Data
abstract
Parallel coordinates are commonly used for non-temporal multivariate data, but there is little support for their usability for displaying temporal multivariate data. In this paper, we introduce a study evaluating the usability of 2D and 3D parallel coordinates for pattern identification in temporal multivariate data. The results indicate that 3D parallel coordinates have higher usability, as measured with higher accuracy and faster response time as well as subjective ratings, compared to 2D.
Kahin Akram Hassan, Niklas Rönnberg, Camilla Forsell, Matthew Cooper 0001, Jimmy Johansson 0001
IV (1)2
2019 Musical sonification supports visual discrimination of color intensity
abstract
Visual representations of data introduce several possible challenges for the human visual perception system in perceiving brightness levels. Overcoming these challenges might be simplified by adding sound to the representation. This is called sonification. As sonification provides additional information to the visual information, sonification could be useful in supporting the visual perception. In the present study, usefulness (in terms of accuracy and response time) of sonification was investigated with an interactive sonification test. In the test, participants were asked to identify the highest brightness level in a monochrome visual representation. The task was performed in four conditions, one with no sonification and three with different sonification settings. The results show that sonification is useful, as measured by higher task accuracy, and that the participant's musicality facilitates the use of sonification with better performance when sonification was used. The results were also supported by subjective measurements, where participants reported an experienced benefit of sonification.
Niklas Rönnberg
Behav. Inf. Technol.1