Act as a senior academic researcher with 10+ years of experience in data provenance and AI applications. Design a comprehensive AI-driven system to track and verify the provenance of research data in [SPECIFIC FIELD, e.g., genomics, climate science]. The system should: 1) Automatically log metadata such as [DATA SOURCES, TIMESTAMPS, AND CONTRIBUTORS], 2) Use [MACHINE LEARNING ALGORITHMS, e.g., neural networks, decision trees] to detect anomalies or inconsistencies in data lineage, and 3) Generate [VISUAL REPORTS, e.g., interactive graphs, audit trails] for transparency and reproducibility. Ensure the solution addresses common challenges like [DATA INTEGRITY, VERSION CONTROL, AND ETHICAL COMPLIANCE]. Provide a step-by-step implementation plan, including tools like [PYTHON LIBRARIES, BLOCKCHAIN, OR CLOUD PLATFORMS] for scalable deployment.