Digital DNA: A Computational Paradigm for Self-Governing Data

We present Digital DNA, a computational paradigm where data units ("datums") possess biological properties enabling self-governance, self-correction, and controlled self-destruction. Unlike conventional architectures treating data as passive material, Digital DNA treats data as living entities with ten properties derived from molecular biology — including genome, metabolism, immunity, lifecycle, and adaptation. The paradigm introduces structural safety constraints embedded in the data substrate itself rather than enforced by external policy layers. A working prototype has been implemented and tested. This paper describes the theoretical framework, the ten properties, and implications for autonomous systems, AI safety, and computational economics.