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TIBA: A web application for the visual analysis of temporal occurrences, interactions, and transitions of animal behavior.
- Source :
- PLoS Computational Biology; 10/25/2024, Vol. 20 Issue 10, p1-18, 18p
- Publication Year :
- 2024
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- BIG data
WEB-based user interfaces
SOURCE code
ANIMAL behavior
BEHAVIORAL research
Subjects
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 20
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 180502868
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1012425