📅 2023-05-01 — Session: Developed Data Policy Framework for Academic Institutions
🕒 22:40–23:10
🏷️ Labels: Data Policies, Academic Collaboration, Data Management, Interdisciplinary, Data Science
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop a comprehensive framework for data policies within academic institutions to enhance research capabilities and interdisciplinary collaboration.
Key Activities
- Drafted a discourse on data policies emphasizing internal coordination and data science training.
- Proposed a roadmap for data management, including internal and external data analysis, coordination, and training.
- Reflected on the impact of data science departments and the need for mindset shifts to foster collaboration.
- Discussed challenges in accessing institutional data and the necessity of clear data policies for research.
- Advocated for a normative framework to regulate data management, ensuring privacy and security.
Achievements
- Established a clear proposal for data policy elements, including coordination and training.
- Developed a roadmap for data management strategies within the faculty.
- Highlighted the transformative potential of data science in academic settings.
Pending Tasks
- Finalize the normative framework for data management and present it to the faculty committee for approval.
- Implement training programs for faculty members on data policies and management.
- Foster interdisciplinary collaboration through workshops and seminars on data science.