Hosted by the Lucy Family Institute for Data & Society and the Berthiaume Institute for Precision Health, the Health Equity Data 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.
Register for the info session (Sep 20 at 1 pm on Zoom)
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; register here |
| 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:
- 10-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.