Important Dates for the Winter 2019 Incubator:
Thursday, October 25th, 1pm: Information meeting. Location: WRF Data Science Studio, 6th floor Physics/Astronomy Tower.
Friday, November 9th: Applications due. CLICK HERE TO APPLY
Monday, December 3rd: Notification of proposal selections.
Tuesday, January 8th: Kickoff meeting. Location: WRF Data Science Studio.
Get an overview of the Winter Incubator here: http://escience.washington.edu/get-involved/incubator-programs/overview/
If you have any questions about submitting a project for an Incubator, please consult one of our data scientists during their office hours for guidance: http://escience.washington.edu/office-hours
The application form will ask for the following information:
- Contact information for the project lead — the one who will join us in the studio and be responsible for carrying out the project.
- A description of your data. At least the size, formats, where the data currently resides, and any privacy and access restrictions. We strongly favor projects that have already collected the relevant data rather than “preparatory” projects that involve building software in the anticipation of future data collection activities.
- Project summary / objective (~1 page) similar to the Specific Aims sections in NIH and NSF proposals. This document should include the key science questions the data will help answer and the key technical challenges you face in answering these questions. For example: Do you need new methods or algorithms? Do you need to scale up existing methods? Do you need to integrate data so it can be analyzed? Do you need to publish data and/or code to improve collaborative opportunities and reproducibility?
- Tips on how to write in this style can be found here:
Proposals are prioritized based on the following criteria:
Good clustering between proposals; ideally, we seek a cohort of proposals with a common theme
Alignment with sponsor and program goals
Participant availability and engagement
Ability to answer fundamentally new research questions
Clarity and shovel-readiness
Capacity for measurable outcomes
Capabilities of the incubator staff