Rapid advancements in scientific technologies provide new opportunities to facilitate discoveries while posing challenges in managing and analyzing large and complex data sets. To advance data intensive discovery, this week-long scientific barnraising provides teams of participants the opportunity to work with interdisciplinary faculty to advance their scientific endeavors. Our goals are to identify projects, perform preliminary analyses, and implement software that forms the structural components of a scientific endeavor that participants will continue to pursue subsequent to the event.
Why a barnraising?
We propose a barnraising to contrast with a hackathon. Hackathons can be construed to include an emphasis on quick and superficial programming. This barnraising is designed to provide more substantial support for projects.
Fields of expertise.
In 2014, the Gordon and Betty Moore foundation, recognizing the increasing role of data intensive techniques in the scientific process, designated 14 “Moore Investigators in Data-Driven Discovery”. These investigators come from diverse fields including mathematics, biology, visualization, astrophysics, and others. We have leveraged this network to recruit an initial set of trainees for this scientific barnraising. Applications by trainees from outside of this network will be considered and may be approved on a space-available basis.
A trainee-driven barnraising.
We are leveraging the network of Moore Investigators to bring together trainees and faculty from this community. This network will provide a set of trainees with expertise in diverse scientific and technical domains, but trainees are also likely to share a common set of skills related to programming and software engineering. Trainees will have an opportunity to meet participants, develop teams, and plan projects through an online discussion system within the month before the event. During the event, trainees will work in self-organized teams to implement the infrastructure or scientific project that they have planned. Trainees are expected to develop and execute projects in teams, and faculty are present to help trainees plan the implementation and sustainability phases of the project.
- Casey S. Greene, Ph.D.Assistant ProfessorUniversity of Pennsylvania
- Benjamin L. King, Ph.D.Senior Staff ScientistMDI Biological Laboratory
- Blair D. Sullivan, Ph.D.Assistant ProfessorNorth Carolina State University
- Matthew J. Turk, Ph.D.Research ScientistNational Center for Supercomputing Applications
Casey S. Greene is an Assistant Professor at the University of Pennsylvania. His lab develops and applies machine learning methods for integration of large-scale data compendia. His research is primarily funded by the Gordon and Betty Moore Foundation, The National Science Foundation, and the Cystic Fibrosis Foundation.
Blair D. Sullivan is an Assistant Professor at North Carolina State University. Her research group, Theory in Practice, develops and applies efficient structure-exploiting algorithms for the analysis of large-scale networks. Her research is primarily funded by the Gordon and Betty Moore Foundation and the Defense Advanced Research Projects Agency GRAPHS program.
Matthew Turk is a Research Scientist at the National Center for Supercomputing Applications (NCSA) at the University of Illinois and a Research Assistant Professor in the Astronomy department at UIUC. His research is primarily funded by the Gordon and Betty Moore Foundation.
Benjamin L. King is a Senior Staff Scientist at MDI Biological Laboratory. His research applies computational techniques to understand the mechanisms of biological processes in a variety of organisms. Biological processes arise through a complex network of interactions between genes, proteins, metabolites, and environmental factors. Current projects involve using genome-level data to build and analyze these networks. His research is primarily funded by the National Institutes of Health.
Structure of the event.
Trainees will be expected to make lightning presentations during the introductory session covering skills and interests. From that point, trainees will identify collaborators, design projects, and design and implement analytical solutions. Faculty organizers will facilitate project development, guide discussions, and provide advice to address challenges that arise.
Rough Schedule, subject to change:
* April 4: open discussion channel for participants (introduction, planning).
* April 15: form groups via online discussion & decide general projects.
* April 29: outline group-specific goals for the barn raising.
* May 1: arrive at MDI Biological Laboratory, 3:00pm housing check-in, eat dinner, launch barn raising.
* May 2-5: implement planned projects, present daily updates.
* May 6: create sustainability plan and/or triage project and construct post-mortem. Depart MDI Biological Laboratory.
* May 16: first sustainability check in via online discussion.
* May 30: second sustainability check in via online discussion.
* July 15: third sustainability check in via online discussion.
Housing is included in tuition. Dormitory accommodations are assigned double occupancy. Single occupancy rooms, if available, can be purchased for an additional cost.