📅 2023-03-06 — Session: Developed data policies for university collaboration
🕒 17:30–20:30
🏷️ Labels: Data Policies, Collaboration, Data Management, University, Public Sector
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop comprehensive data policies to enhance collaboration between universities and public offices, focusing on data management, privacy, and ethical use.
Key Activities
- Reviewed methods for estimating treatment effects using matched data and difference-in-differences (DID) estimators.
- Discussed statistical tests such as paired t-tests and Wilcoxon signed-rank tests for treatment effect estimation.
- Explored data visualization techniques using Python libraries Matplotlib and Seaborn.
- Planned data policies for universities, including data privacy, security, and compliance.
- Developed frameworks for data management offices in universities, emphasizing multidisciplinary collaboration.
- Outlined strategies for academic-public partnerships in data science, focusing on interdisciplinary cooperation and continuous education.
Achievements
- Established a framework for data policy development in universities.
- Highlighted the importance of interdisciplinary collaboration and continuous education in data science.
- Summarized key innovations from collaborative projects between universities and government agencies.
Pending Tasks
- Finalize the data policy framework and ensure alignment with legal and ethical standards.
- Implement the strategies for fostering collaborations between academic faculties and public offices.