The NIH will host a Learning and Testing Data Science hackathon on February 23rd, 2018 on the main campus in Bethesda, MD. Learners will test alpha and beta code that have been generated in full, collaborative development hackathons for a wide range of scientific problems, including general bioinformatics and genomic analyses in addition to text, image, and sequence processing. This event is for researchers who are in the early stages of their data science journey, including students and postdocs. Other non-scientific developers, mathematicians, or librarians in a similar educational place are also welcome! Learning in this event will be primarily hands-on and self-driven, but will also include short workshops on topics such as Docker and GitHub. Mentors will also be available to assist with questions.
To be considered for the event, potential participants must submit an application and indicate their willingness to travel to the main NIH Campus in Bethesda (see details below).
The hackathon will consist of teams of two to three individuals. These teams will run tools developed at previous NIH hackathons, including novel bioinformatics pipelines and tools to analyze large datasets within a cloud infrastructure. Based on their experiences and issues with running the tools, teams will submit GitHub issues and provide feedback and input by submitting a GitHub pull request. Students will also be encouraged to get involved by assisting with code documentation, error handling ,and container modification (for more advanced learners). Potential tools to be considered in this hackathon include:
Please see the application form for more details and additional projects. The project list will continue to evolve and will be updated on the application form.
After a brief organizational session, teams will spend one day working on a challenging set of scientific problems related to a group of datasets. Participants will analyze and combine datasets in order to work on these problems.
Datasets will come from public repositories or will be supplied by the organizer. During the hackathon, participants will have an opportunity to include other datasets and tools for analysis. Please note, if you use your own data during the hackathon, we ask that you submit it to a public database within six months of the end of the event.
To apply, complete this form. Applications are due Monday, February 12th, 2017 by 11:59 pm ET. Participants will be selected based on their experience and motivation they provide on the