Open Science for Synthesis is a unique bi-coastal training offered for early career scientists who want to learn new software and technology skills needed for open, collaborative, and reproducible synthesis research.
UC Santa Barbara’s National Center for Ecological Analysis and Synthesis (NCEAS) and University of North Carolina’s Renaissance Computing Institute (RENCI) will co-lead this three-week intensive training workshop with participants in both Santa Barbara, CA and Chapel Hill, NC from July 21 - August 8, 2014. The training is sponsored by the Institute for Sustainable Earth and Environmental Software (ISEES) and the Water Science Software Institute (WSSI), both of which are conceptualizing an institute for sustainable scientific software.
Participants receive hands-on guided experience using best practices in the technical aspects that underlie successful open science and synthesis – from data discovery and integration to analysis and visualization, and special techniques for collaborative scientific research, including virtual collaboration over the Internet. A dynamic group of instructors have been assembled to provide for a mixture of instructive lectures, discussions forums, exercises, and real world application of skills to synthesis projects.
This Open Science training revolves around scientific computing and scientific software for reproducible science. We will emphasize the integration of statistical analysis into well-documented workflows through the use of open-source, community-supported programming languages. And, we will promote skills for rapid and robust implementation of open source scientific software. These approaches will be explored and applied to ecological, environmental, evolutionary, Earth and marine science synthesis.
The course weaves together several core themes which are reinforced – and injected into the real-time synthetic scientific research process – through daily work on group synthesis projects. Core training themes will address:
- Collaboration modes and technologies, virtual collaboration
- Data management, preservation, and sharing
- Data manipulation, integration, and exploration
- Scientific workflows and reproducible research
- Agile and sustainable software practices
- Data analysis and modeling
- Communicating results to broad communities
In addition, throughout the course we will maintain a strong emphasis on computing fundamentals, with the intent of providing all participants with a solid foundation for doing synthetic research in today’s computational- and data-intensive era. This includes:
- Instruction on many aspects of R for data manipulation, analysis, and visualization
- Survey of general programming constructs, paradigms, and best practices
- Exposure to the Linux/UNIX command line environment and useful tools
- Demystification of modern computers that have bearing on effective science
- Discussion of cyberinfrastructure trends supporting open, networked, reproducible science
Participants will organize into synthesis teams that focus daily on utilizing the software skills taught during this workshop in the context of cross-cutting science research projects. Applicants will be asked to suggest topics for synthetic research, and these will inform the projects chosen for the workshop. Participants will use an open community engagement process that can maximize success in collaborative research and, depending on the research topics, could lead to publishable results.