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


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
Oct 2024
Historique:
received: 07 09 2023
accepted: 19 08 2024
medline: 25 10 2024
pubmed: 25 10 2024
entrez: 25 10 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39453883
doi: 10.1371/journal.pcbi.1012425
pii: PCOMPBIOL-D-23-01435
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1012425

Informations de copyright

Copyright: © 2024 Kraus et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Nicolai Kraus (N)

Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

Michael Aichem (M)

Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

Karsten Klein (K)

Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

Etienne Lein (E)

Behavioural Evolution Research Group, Max Planck Institute of Animal Behavior, Konstanz, Germany.

Alex Jordan (A)

Behavioural Evolution Research Group, Max Planck Institute of Animal Behavior, Konstanz, Germany.

Falk Schreiber (F)

Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.
Faculty of Information Technology, Monash University, Melbourne, Australia.

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Classifications MeSH