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How to establish and maintain a multimodal animal research dataset using DataLad.
Kalantari, Aref; Szczepanik, Michal; Heunis, Stephan; Mönch, Christian; Hanke, Michael; Wachtler, Thomas; Aswendt, Markus.
Affiliation
  • Kalantari A; University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany.
  • Szczepanik M; Psychoinformatics Lab, Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
  • Heunis S; Psychoinformatics Lab, Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
  • Mönch C; Psychoinformatics Lab, Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
  • Hanke M; Psychoinformatics Lab, Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
  • Wachtler T; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
  • Aswendt M; Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, München, Germany.
Sci Data ; 10(1): 357, 2023 06 05.
Article in En | MEDLINE | ID: mdl-37277500
ABSTRACT
Sharing of data, processing tools, and workflows require open data hosting services and management tools. Despite FAIR guidelines and the increasing demand from funding agencies and publishers, only a 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 was introduced to ensure data security in addition to a homogeneous file and folder structure. Changes to the data were automatically tracked using DataLad and all data was shared on the research data platform GIN. This simple and cost-effective workflow facilitates the adoption of FAIR data logistics and processing workflows by making the raw and processed data available and providing the technical infrastructure to independently reproduce the data processing steps. It enables the community to collect heterogeneously acquired and stored datasets not limited to a specific category of data and serves as a technical infrastructure blueprint with rich potential to improve data handling at other sites and extend to other research areas.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Animal Experimentation / Datasets as Topic Limits: Animals Language: En Journal: Sci Data Year: 2023 Type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Animal Experimentation / Datasets as Topic Limits: Animals Language: En Journal: Sci Data Year: 2023 Type: Article Affiliation country: Germany