Developed data policies for university collaboration
- Day: 2023-03-06
- Time: 17:30 to 20:30
- Project: Business
- Workspace: WP 1: Strategic / Growth & Development
- Status: In Progress
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Data Policies, Collaboration, Data Management, University, Public Sector
Description
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.
Evidence
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- event_ids: []