Data Management in Forensic Medicine: A Proposal for a Layered Architecture Model

Forensic medicine has undergone a digital transformation. As this field becomes more data-driven the underlying data has emerged as a critical determinant. Therefore, a well-composed data management is essential for ensuring that digital forensic workflows are both scientifically sound and legally defensible. This article aims to synthesize current literature on data management in forensic medicine, as well as sources of challenges and mitigation strategies. In result, an overarching layered data management architecture is constructed, based on 12 peer-reviewed publications. The systematic literature review following the PRISMA guidelines was conducted in autumn 2025, spanning the period from January 2004 to August 2025. Pubmed including MEDLINE and IEEE xplore were used as academic databases, by using the searchstrings i.a. "forensic medicine", "data management", "data quality", "data governance" or "information system" in titles, abstracts, keywords and full text. Drawing from the current literature, interoperable, and ethically governed forensic data systems, an eleven-layer data management model was developed. To critically evaluate the applicability of the proposed data-management model, recurring limitations reported in the reviewed literature were mapped against corresponding mitigation measures derived from both empirical insights and design principles. Overall, the mitigation strategies demonstrate that many of the systemic weaknesses in current forensic data ecosystems can be addressed through deliberate architectural and governance design. By embedding standardized data models and strong privacy controls into a layered structure, the proposed model not only enhances data integrity and interoperability but also strengthens the legal defensibility and ethical accountability of forensic processes.