Privacy and Data Integrity in Digital Pharmacognosy - A Localised Architecture for Sensitive Medical Research

Abstract

The integration of digital technologies into pharmacognosy has enabled researchers to process vast amounts of historical botanical data and ancient medical manuscripts. However, the current reliance on cloud-based extraction tools and third-party servers introduces critical vulnerabilities regarding data privacy, intellectual property protection, and regulatory compliance. When researchers process sensitive pharmacological data—such as undiscovered herbal compounds or indigenous traditional medicine formulas—using external cloud services, they risk exposing unpatented intellectual property and violating institutional data governance policies. This paper proposes a paradigm shift towards a localised, privacy-first architecture for digital pharmacognosy research. By adapting enterprise-grade network security principles, this framework ensures that all data extraction, optical character recognition (OCR), and structural metadata compilation occur entirely on the researcher's local machine. This approach not only mitigates the risk of data exfiltration but also aligns with the FAIR Data Principles by maintaining strict access controls. The paper concludes that adopting localised infrastructure is essential for preserving the integrity and confidentiality of sensitive medical research in the digital humanities.