I will thank you for having me be part of this conference.
My name is Sarah Stone.
I'm the executive director at the eScience Institute at the University of Washington,
where we run a variety of programs to help researchers across all fields use and
develop data science tools and techniques.
I'm also representing the West Big Data Innovation Hub.
I have a poster in the lobby because I can't talk about it now.
So the program I am gonna focus on today is our Data Science For Social Good program,
and we've been running this program since the summer of 2015.
It runs during the 10-week summer quarter and so we'll be heading into our fifth summer this year.
And this program brings together student fellows and researchers,
really from a variety of different disciplinary and methodological backgrounds,
that come together to work on focused collaborative projects with societal benefit.
And so just giving you a feel for the program, each summer we bring together three to four project teams,
and this is what the team consists of.
So we have one to two project leads.
The project leads are the people who submitted the proposal.
We take proposals from within academia, nonprofits, government, industry.
And we've had all of those different groups represented over the course of the past four years.
The project lead is required to spend the equivalent of two days a week
working in the studio with the team for the duration of the summer.
And that's a pretty hard and fast requirement and while we recognize that
that limits the projects that we're going to get, because we're getting a lot of projects from our local area,
we feel that that integration of the project lead into the project team keeps the team focused.
It keeps us more likely to be using the data responsibly and ethically,
and so that's one of the key foundations of our program.
We also have one to two of our eScience data scientist staff, who are part of these project teams.
They're the backbone of all the programs that we run at the eScience Institute.
They're a really wonderful crew of people who come up from a variety of different disciplines.
We see this in data science but they got really excited about developing tools for their discipline.
So they work very readily across disciplinary spaces and they help to support this program.
Lastly, we have the student fellows.
And so each team has four to five student fellows.
We do a national call for student fellows.
Most of the student fellows are graduate students but about 20% are advanced undergraduates.
And so these teams come together.
I didn't mention, so we've supported projects in a variety of different spaces.
We think of data science for social good very broadly,
so we've done projects around transportation, public health, homelessness, education, access issues.
The program activities are structured,
and we have the a wide variety of technical tutorials that are front-loaded.
We take students who come with a variety of different technical, or levels of technical expertise.
We do require some programming background of all the students,
but we consider it an asset to have students who are bringing both different disciplinary backgrounds
and also different levels of technical expertise,
and we don't require sort of a particular programming language like some other sort of similar programs do,
because we think that variety actually lends itself very nicely to the project teams.
And so we do have some technical tutorials to get everybody more on a level playing field
and to some extent,
we can address those technical tutorials towards the particular projects that we're supporting that year.
In some cases, we often have a lot of projects that require GIS
and so we'll do tutorials around that space, for instance.
We're also very fortunate to have ethnographers and human centered data scientists integrated into our staff,
and so they've developed a curriculum.
Oh boy, I just got my one minute.
They've developed a curriculum around a very complete stakeholder identification from the stakeholders
who are very readily and interacting with the project teams, all the way out to distant end users.
And also thinking on a project based, in a project-based way, about the ethical implications of that project.
I'm gonna jump to the next slide.
Over the past four years, we've brought on 63 student fellows.
Just to give you an idea of the Disciplinary breadth,
about 60% of our students come from STEM fields, 40% from non-STEM.
We think this mix of people with methods backgrounds, social science,
and then environmental physical sciences, really lends itself to an interesting project team dynamic.
And actually I'm gonna jump to this one, I'll come back to that,
and what we hear from the students is that the most valuable part of this program
is getting to collaborate with students across disciplines.
And I'm getting my stop sign.
[laughing]
But I will leave this the last slide up so you can read it as we're transitioning,
but these are the projects we hosted last year, just to give you an idea of the type of things we do.
Thanks very much.
[clapping]