Hackathons as a means of accelerating scientific discoveries and knowledge transfer

Area of Science:

• Biomedical research
• Computational biology
• Data science

Background:

• Scientific research advances knowledge and solves societal challenges, often within institutions.
• Collaborative science across institutions is common, but data analysis may lack oversight.
• Traditional data analysis separates data generators and bioinformaticians.

Purpose of the Study:

• To demonstrate how hackathons can enhance collaborative science.
• To improve the peer review and reproducibility of scientific analyses.
• To bridge the divide between data generation and bioinformatic analysis.

Main Methods:

• Utilizing hackathons to foster collaboration between researchers.
• Implementing cross-validation of study designs and datasets.
• Driving reproducibility through shared analytical workflows.

Main Results:

• Hackathons enable peer review before publication of analysis results.
• Hackathons improve the cross-validation of study designs and datasets.
• Hackathons promote the reproducibility of scientific analyses.

Conclusions:

• Hackathons serve as a valuable tool for enhancing collaborative science.
• Hackathons provide a platform for agile extension to structured collaborations.
• Hackathons facilitate integration between data generators and bioinformaticians for robust analysis.