Hosted by the Lucy Family Institute for Data & Society and the Berthiaume Institute for Precision Health, the Health Equity Data Science Challenge is an opportunity for student teams to tackle an interesting, data-driven question related to health equity.
Over the course of a month, participants will design a project that utilizes one or two of several provided datasets, with guidance and feedback from a panel of graduate students and faculty. The challenge culminates in project presentations to peers, faculty, and industry leaders.
An info session was held on Sep 20. If you would like access to the recording or the slides, please email Dr. Katie Liu (kliu22@nd.edu).
Benefits:
- Societal Impact: Explore open questions in health equity with real-world datasets.
- Networking: Present your findings to academic and industry leaders.
- Resume Building: Option to create a data story or dashboard that you can publish on the dataMichiana website.
- Cash Prizes: The winning team will receive $2500 and two runner-up teams will each receive $1000.
Important Dates:
| Date | Details |
|---|---|
| Sep 20 | Info Session at 1 pm on Zoom |
| Oct 4 | Deadline to sign-up |
| Oct 7 | Challenge kick-off meeting at 5 PM; datasets and detailed instructions will be released |
| Oct 8-31 | Intermediate meeting with graduate student mentor |
| Nov 1 | Intermediate Pitch: Propose your project (including datasets to be used and the main question), provide preliminary results to a panel of graduate students/faculty, and receive feedback. |
| Nov 4-14 | Practice presentation with graduate mentor |
| Nov 15 | Final presentations to graduate student/faculty panel and industry leaders |
Eligibility:
All participants must be currently enrolled Notre Dame or Saint Mary’s undergraduate students.
All teams must have at least 2 representatives present at the Final Presentations, which will take place on Friday, November 15 from 1-4 PM.
Teams:
- Create a team of 2-4 students to work with
- Sign up via link – only one submission per team is necessary. Please make sure that your teammates have agreed before you list their names.
- If you don’t have a team, please indicate this on the sign-up form. We will try to match you with 1-3 other students who have also signed up as individuals.
Final Project Information:
Presentation:
- 8-minute slide presentation with dataset, question, methods, results/discussion, and conclusion. The best presentations will be data-driven narratives, so tell a story with the data!
- The format is flexible, including slides, data dashboard presentation, html/markdown, etc. Should include figures, maps, other visualizations, etc.
Data/Code:
- Code used should be well annotated/commented, and publicly available (e.g. on github). A link to access code should be provided in the presentation.
- Any language or data analysis techniques can be used, although R and python are encouraged.
Scoring Rubric:
Projects will be judged by a panel of graduate students and faculty who will independently score projects before an aggregation of the scores will be used to calculate winners. The scoring rubric is available here.
