Data Science Across Disciplines: A Focal Point Project Diana M. Byrne 1, Halie M. Rando 2, Heidi J. Imker 3, Ayla Stein 3 1 Department of Civil and Environmental Engineering, 2 Department of Animal Science, 3 University Library, University of Illinois at Urbana-Champaign, Urbana, IL Data Skills Development Motivation Jeremy Guest (Diana’s advisor) and Anna Kukekova (Halie’s advisor) Graduate School of Library and Information Science (GSLIS) University Library (especially Ian Harmon) Research Data Service (RDS) Illinois Informatics Institute (I3) Graduate College and the Focal Point initiative for funding The speakers (Drs. Andrade, Brown, Green, Lane, Turk, and Work) Focal Point Participants! Final Project When each student was asked whether their advisor had ever helped them learn a programming skill (including Excel), students responded: No (12) Baseline Understanding (%) Understanding after Lesson (%) Choose a dataset: Students chose a dataset from their own research projects. Come up with a question: Students asked an interesting question of their datasets. Pick a language: Students identified the language(s) that was the best fit for their project. Determine methods and get results: Students wrote the code they needed to complete their project. Present final work as a poster: Students are showcasing their projects at the final poster session. Chad Lane Educational Psychology, Illinois Informatics Institute Nicole Brown National Center for Supercomputing Applications Matt Turk Astronomy, National Center for Supercomputing Applications Dan Work Civil and Environmental Engineering Flavia Andrade Kiniseology and Community Health, Applied Health Sciences Harriett Green English and Digital Humanities Librarian Speakers from Across Campus Student Improvement and Comments “[My advisor] told me to talk to more experienced students, who have been helpful. However, from starting this class, I realize many of the techniques I have been taught from older students are inefficient.” “Now I can clean my data or find trends quickly! I was spending so much time on things that literally take 30 seconds now that I format, filter, then sort my data in ways I had never thought of before!” “I particularly enjoyed how you incorporated the problems that people in the class were having in their own data and showed solutions with how to deal with those problems.” “[This class was] super relevant, as in I learned things that I have now been using on a daily basis to make my research/life easier.” “Thanks for an awesome semester, I learned so much! I have always been scared of coding and this has made it much more accessible.” 1.Create a cohort of graduate students aware of the importance of data science to research, proficient in data management techniques, and ready to apply basic data science principles to their own work Thank You The amount of data available across disciplines is exploding. Data science focuses on the process by which information is extracted from data; therefore, it is relevant to all areas of research, not just computational fields. Illinois has a wealth of researchers from across fields using data in innovative ways applicable to their research, which graduate students can learn from. Objectives Each participant has addressed a challenge in her/his own graduate research using programming. You are encouraged to talk to presenters about how they handled their problem before this semester and how their new solution will benefit their research The Posters Data science is growing rapidly and data scientists are one of the most in-demand professions for However, not everyone is given an equal opportunity to learn fundamental data science skills, especially programming. Women and racial minorities are dramatically under- represented in computer science classrooms at the university level, but students who do not identify with the stereotypical image of a “programmer” can still benefit from and excel at these skills. Yes (2) No (14) Data science is becoming increasingly important across fields Data science skills are an area of critical need for graduate students 2.Implement an explicit code of conduct to foster a supportive and compassionate environment 3.Teach data analytic and management skills through lectures and problem sets (first semester) and project-based learning (second semester) 4.Host speakers from across campus who use data in creative ways to explore existing research and inspire participants Please remember that for many people, the Focal Point has been their first introduction to programming and this project is their first attempt to design and implement their own programming- based solution to a challenge. We hope you enjoy learning about their work! very comfortable very comfortable not comfortable somewhat comfortable somewhat comfortable Graduate students learned data analytic and management skills in Excel, Matlab, and Python