All Colleges were invited to nominate 2019-2020 Data Science Ambassadors. Deadline June 1, 2019.
2018-2019 Data Science Ambassadors: Champions for Data Science Literacy
--Kristy Makansi, RDI Communications
From astronomy to zoology, researchers use data to better understand their subject areas, develop and test hypotheses, and make new discoveries. But not every researcher is a data science expert. That’s where the Data Science Ambassadors come in.
Data Science Ambassadors (DSAs) are graduate students with the requisite knowledge and expertise to help researchers in their respective colleges develop data science skills. With a $1,000 stipend for an academic year commitment, DSAs receive training and support as they work to help others in their subject areas tap into the potential of data science.
Under the direction of Jeffrey Oliver and Vignesh Subbian, the DSA program is currently supported by and offered in the Colleges of Agriculture & Life Sciences, Engineering, Science, and Social & Behavioral Sciences.
Brian Maitner, a DSA in the College of Science, is a PhD student in Ecology & Evolutionary Biology who studies the processes that generate and maintain biodiversity at a global scale. Data science is critical to his field because “a single person can’t possibly collect the type of data needed to address the questions I’m interested in. Data science is needed to cobble together enough data in a useful way to address global questions.”
As an ambassador, Brian has provided coding help, particularly emphasizing Open Source solutions, and is running a weekly NetLogo workshop. Additionally, he’s working with the Introductory Biology Lab Director, Ryan Ruboyianes, to develop simulations that students can run on their own computers and smart phones and that help clarify some of the important ideas presented during lab.
A phenoclimatologist in the School of Natural Resources and Environment and the Laboratory of Tree-Ring Research, Amy Hudson is a DSA in the College of Agriculture and Life Sciences. As part of her DSA work, she and another ambassador, Jiali Han, have been instrumental in helping organize the first Women in Data Science – Tucson event. Hudson is grateful to the role other researchers have played in helping her learn to code and to “untangle an analysis.” Being an ambassador, she says, is a way to “pay these actions of mentorship forward in a more structured framework.”
Since becoming an ambassador, Hudson has been an instructor for two Data Software Carpentry workshops, including one titled Geospatial Lessons in R. When she arrived at the classroom on the first day, she saw that six of the 30 learners were fellow students in her department. She jumped in and approached the course as a cohort event. “We were laughing and groaning over learning this new skill together. Everyone was supporting each other, and it really made me proud and happy to be there to help out.”
For Joseph Long, whose work focuses on high-contrast astronomical imaging in the search for exoplanets, data science is one of the tools that makes his work possible.
“Data science is an umbrella term for a set of computational and statistical techniques, combined with the infrastructure for applying them to large data sets,” Long says when asked to describe data science. And Long certainly works with large data sets. His current project involves applying dimensionality reduction techniques to sequences of tens of thousands of images of a single star to model patterns of starlight and then subtract those patterns in the hopes of revealing a planet in the star’s orbit.
One of the ways Long is helping others leverage the power of data science in their own work is to get people out of their offices to share challenges, lessons learned, and insights gained.
“In addition to organizing a monthly talk/tutorial series on computing topics that is open to the whole university community, I set up a Slack channel to facilitate sharing questions and fostering discussion within our graduate student Slack organization.”
For Maitner, Hudson, and Long, participating in the DSA program is an effective way to spread the word about data science while also enhancing their understanding of the tools that enable their own work. Other DSAs include Jiali Han (College of Engineering), Xiang Liu (College of Agriculture & Life Sciences), Don Merson (College of Social and Behavioral Sciences), Matt Miller (College of Science), and Cristian Román-Palacios (College of Science).
If you would like to work with a DSA, submit a request at firstname.lastname@example.org. If you would like your college to get involved in the DSA program, please contact one of the program directors for information.
Jeffrey Oliver, email@example.com
Vignesh Subbian, firstname.lastname@example.org