ß ß Data Science Incubator

This morning Context: A Data Science Environment Data Science Studio Pilot Incubator Program Discussion 2

A 5-year, $37.8 million cross-institutional collaboration 3

Establish a virtuous cycle 6 working groups, each with 3-6 faculty from each institution

Pilot Program Organizers Andrew Whitaker, Research Scientist Dan Halperin, Director of Research, Scalable Data Analytics Jake Vanderplas, Director of Research, Physical Sciences Bill Howe, Associate Director 5

The Data Science Studio An open collaborative research space A resident data science team – Permanent staff of ~5 data scientists – applied research and development – ~15-20 data science fellows (research scientists, visitors, postdocs, students) How to Engage: – Drop-in open workspace – Studio “Office Hours” – Incubation Program …plus seminars, sponsored lunches, workshops, bootcamps, joint proposals... 6

7 6 th floor Physics Astronomy Building A partnership among … Provost UW Libraries Physics, Astronomy, Arts & Sciences eScience Institute

8 Estimated Timeline: Design Phase Jan-June Construction June – Sep Target: October 1, 2014

Incubator Program Overview Goal: Create watercooler opportunities and scale our efforts by co-locating collaborations from different fields in the studio Protocol: ~1-page proposals for 1-quarter, on-site data science collaborations with us What we're looking for: Projects where fruitful collaboration is possible, with potential for significant impact, and that have sustained engagement This meeting: Pilot program for Spring Quarter to inform full launch Fall

Spring Incubator Pilot Program Logistics Applications due online 3/10 Each proposal identifies a Project Lead (PL) – The person doing the work, not the thesis advisor Incubator participants join the studio 2 days/week – Days decided collectively by participants and team Pilot program operates out of Sieg 326 Milestones at 3, 6, 9 weeks – blog posts + demo, visualization, IPython notebook, dataset, GitHub repo, preliminary results, etc. Networking/poster session during 9 th week 10

Areas of interest scalable data management and analytics learning and predictive models interactive visualization parallel algorithms code review, publishing, and reproducibility online teaching materials, tutorials 11

A Live SeaFlow Dashboard 12 Laser Microscope Objective Pine Hole Lens Nozzle d1 d2 FSC (Forward scatter) Orange fluo Red fluo Francois Ribalet Jarred Swalwell Ginger Armbrust

SeaFlow Ambitions SeaFlow is a huge success! NSF wants one on every R/V 13

SeaFlow Ambitions Underway biology should enable adaptive sampling - a sort of “holy grail” How can remote collaborators participate? What about citizen science? 14 “Wait! We saw a population change between P3 and P4!” “Let’s go back!”

A Live SeaFlow Dashboard 15 Is the instrument working? Is the instrument working? Where is the ship? What is it doing? Where is the ship? What is it doing? What phytoplankton populations are we seeing?

The AscotDB Project 16 A multi-year collaboration between UW Astronomy and UW Computer Science researchers and students ASCOT = the AStronomy COllaborative Toolkit Goal: Provide an interactive and collaborative environment for analysis of astronomical data.

The AscotDB Project 17 Interacting browser-based widgets for generating database queries & associated visualization. The resulting visualizations can be shared with collaborators through a browser URL

Pilot cohort desiderata good clustering alignment with sponsor and program goals new directions, new questions availability, engagement, commitment “do only what we can only do together” – with apologies to Djikstra clarity and shovel-readiness capacity for measurable outcomes 18

Spring Schedule 3/10: Proposals due 3/14: Follow-up requests 3/21: Pilot participants notified 3/31: Spring program start date 4/21: First milestone 5/12: Second milestone 6/2: Third milestone 6/6: Poster/networking event 19