How to establish and maintain a multimodal animal research dataset using DataLad

Sharing of data, processing tools, and workflows require open data hosting services and management tools. Despite FAIR guidelines and increasing demands from funders and publishers, few animal studies share all experimental data and processing tools. We present a step-by-step protocol to perform version control and remote collaboration for large multimodal datasets. A data management plan ensures data security and a homogeneous file/folder structure. Changes to data are automatically tracked using DataLad and all data are shared on the research data platform GIN. This simple and cost-effective workflow facilitates adoption of FAIR data logistics and processing by making raw and processed data available and providing the infrastructure to independently reproduce data processing steps. It enables the community to collect heterogeneously acquired and stored datasets across modalities and serves as a technical blueprint to improve data handling and extend to other research areas.

Aref Kalantari, Michał Szczepanik, Stephan Heunis, Christian Mönch, Michael Hanke, Thomas Wachtler, Markus Aswendt