Ethics and Epistemology in Big Data Research.

Area of Science:

• Biomedical research
• Health services research
• Data science

Background:

• Biomedical innovation increasingly utilizes big data for accelerated research and improved real-world applicability.
• Big data research is widely supported by various stakeholders, including scientists, policymakers, industry, and the public.

Purpose of the Study:

• To examine the ethical, organizational, and technical/methodological concerns associated with big data research in biomedicine.
• To critically evaluate the epistemological implications of big data research and their impact on achieving stated goals.

Main Methods:

• Review of current trends and challenges in big data research.
• Analysis of technical, methodological, and ethical considerations.
• Exploration of epistemological questions raised by big data approaches.

Main Results:

• While technological advancements address some technical issues, significant epistemological challenges remain.
• Ethical implications arise from the fundamental nature of knowledge generated by big data.

Conclusions:

• Sophisticated technologies may not fully resolve the epistemological issues inherent in big data research.
• The core goals of big data research may be questioned due to unresolved epistemological and ethical concerns.