This paper presents a step-by-step protocol for version control and remote collaboration on large multimodal animal research datasets using DataLad and GIN. The authors address the lack of standardized data storage and sharing in animal studies, emphasizing the importance of FAIR data principles. Their workflow incorporates a data management plan, homogeneous file structure, automated tracking of changes, and public data sharing on GIN. This approach facilitates data reproducibility and enables community-based analysis of heterogeneous datasets.
Publisher
Scientific Data
Published On
Jun 05, 2023
Authors
Aref Kalantari, Michał Szczepanik, Stephan Heunis, Christian Mönch, Michael Hanke, Thomas Wachtler, Markus Aswendt
Tags
version control
data collaboration
animal research
FAIR data
data management
data reproducibility
heterogeneous datasets
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