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Data Ethics Case Studies
Small Group Discussions
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Small Group Discussions
Small Group Discussion 1: Using Data to Address Health Disparities
Discussion Focus:
What types of data are most useful for understanding health disparities?
How can data science projects prioritize reducing inequities in healthcare access and outcomes?
What partnerships or collaborations can enhance the impact of such work?
How can researchers address barriers to participation in underserved populations?
What benefits do community partnerships bring to health data science projects?
Small Group Discussion 2: Data Ethics Case Studies (Please go to
Data Ethics Cases Studies
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Small Group Discussion 3: Addressing Barriers to Learning Data Science
Discussion Focus:
What common challenges do health researchers face when learning data science?
How can training programs address time constraints, technical intimidation, or lack of resources?
What strategies promote inclusivity and accessibility in data science education?
How can mentors effectively guide trainees in applying data science to health research?
How can organizations create mentorship opportunities that connect data scientists with health experts?
Small Group Discussion 4. Collaboration Across Disciplines and Building Sustainable Data Science Teams
Discussion Focus:
What strategies promote mutual understanding and shared goals between disciplines?
How can workshops and training programs foster interdisciplinary collaboration?
What skills and roles are essential for a successful health data science team?
How can organizations attract and retain talent in data science for health research?
What are effective strategies for training and mentoring new team members?
Small Group Discussion 5: Supporting Career Pathways in Data Science
Discussion Focus:
How can training programs prepare participants for diverse roles in health data science?
What additional skills, such as project management or communication, are critical for career advancement?
How can institutions attract top data science professionals to work in health research?
What strategies can improve retention and professional development for data scientists?
How can institutions support career growth and satisfaction for interdisciplinary teams?