TIBA: A web application for the visual analysis of temporal occurrences, interactions, and transitions of animal behavior

Data in behavioral research is often quantified with event-logging software, generating large data sets containing detailed information about subjects, recipients, and the duration of behaviors. Exploring and analyzing such large data sets can be challenging without tools to visualize behavioral interactions between individuals or transitions between behavioral states, yet software that can adequately visualize complex behavioral data sets is rare. TIBA (The Interactive Behavior Analyzer) is a web application for behavioral data visualization, which provides a series of interactive visualizations, including the temporal occurrences of behavioral events, the number and direction of interactions between individuals, the behavioral transitions and their respective transitional frequencies, as well as the visual and algorithmic comparison of the latter across data sets. It can therefore be applied to visualize behavior across individuals, species, or contexts. Several filtering options (selection of behaviors and individuals) together with options to set node and edge properties (in the network drawings) allow for interactive customization of the output drawings, which can also be downloaded afterwards. TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. The web application and usage instructions are available at tiba.inf.uni-konstanz.de. The source code is publicly available on GitHub: github.com/LSI-UniKonstanz/tiba.

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Publication Details

Journal
PLoS Computational Biology
Published
2024-10-25
DOI
https://doi.org/10.1371/journal.pcbi.1012425
Citations
4
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
3.68

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article

TIBA: A web application for the visual analysis of temporal occurrences, interactions, and transitions of animal behavior

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4 citations
PLoS Computational Biology
Species Distribution and Climate Change
3.68
article

TIBA: A web application for the visual analysis of temporal occurrences, interactions, and transitions of animal behavior

Falk Schreiber, Karsten Klein, Alex Jordan, Michael Aichem, Etienne Lein, N KRAUS
article en
4 citations

Abstract

Data in behavioral research is often quantified with event-logging software, generating large data sets containing detailed information about subjects, recipients, and the duration of behaviors. Exploring and analyzing such large data sets can be challenging without tools to visualize behavioral interactions between individuals or transitions between behavioral states, yet software that can adequately visualize complex behavioral data sets is rare. TIBA (The Interactive Behavior Analyzer) is a web application for behavioral data visualization, which provides a series of interactive visualizations, including the temporal occurrences of behavioral events, the number and direction of interactions between individuals, the behavioral transitions and their respective transitional frequencies, as well as the visual and algorithmic comparison of the latter across data sets. It can therefore be applied to visualize behavior across individuals, species, or contexts. Several filtering options (selection of behaviors and individuals) together with options to set node and edge properties (in the network drawings) allow for interactive customization of the output drawings, which can also be downloaded afterwards. TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. The web application and usage instructions are available at tiba.inf.uni-konstanz.de. The source code is publicly available on GitHub: github.com/LSI-UniKonstanz/tiba.

PLoS Computational BiologyVol. 20(10)
University of Konstanz (DE), Max Planck Institute of Animal Behavior (DE), Monash University (AU)
Deutsche Forschungsgemeinschaft, Max-Planck-Gesellschaft
Openalex Percentile: Top 7%
Species Distribution and Climate Change
3.68
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