The University of Louisville Journal of Respiratory Infections


Introduction: Data sharing in clinical research is critical for increasing knowledge discovery. Data and software tools should be FAIR: Findable, Accessible, Inter-operable and Re-usable. Many bottlenecks exist in the process of a clinical investigator using shared data including data acquisition and statistical analysis. The objective of this project is to develop a structure for sharing data and providing rapid automated statistical analysis through creation of a pre-packaged, open-source software container.

Methods: We use the open source software container technologies VirtualBox and Vagrant to create a template for sharing clinical data and analysis scripts as a single container. We use a timer to record the time necessary to setup and initialize the software container and view the results.

Results: We have created a template for sharing data and analysis scripts together using open source software container technologies VirtualBox and Vagrant. We found the time needed to initialize the container to be 5 minutes and 36 seconds for a macOS-based machine and 7 minutes and 2 seconds for a Windows-based machine. Containers can be downloaded and executed from any Mac or Windows computer allowing both the reuse of and interaction with the data. This greatly reduces the time and effort needed to obtain and analyze clinical data.

Conclusion: Reducing the time and effort needed to obtain and analyze clinical data increases the time available for data exploration and the discovery of new knowledge. This can be effectively achieved using software containers and virtualization.


The author(s) received no specific funding for this work.



Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.



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