Abstract The transition from location-centric data storage (URL-based) to object-centric autonomy (PID-based) represents a fundamental paradigm shift in global information infrastructure. This paper proposes the "Digital Biosphere" framework, a theoretical and engineering approach that synthesizes FAIR Digital Objects (FDO) with bacterial evolutionary strategies to construct resilient, self-organizing data ecosystems. Drawing on the principles of Biomimetics and Thermodynamics of Computation, we introduce three novel architectural mechanisms: 1. Digital Metabolism & Logic Core Distillation: We propose that truly autonomous digital entities (Active FDOs) must consume computational resources (CPU cycles) to maintain information entropy and structural integrity. This mechanism is applied to Artificial General Intelligence (AGI) through the Regenerative Logic-Core Protocol (RLCP), which decouples static factual storage (in FDOs) from neural reasoning logic, thereby mitigating the "Memory Wall" and parameter entanglement issues in Large Language Models (LLMs). 2. Digital Horizontal Gene Transfer (HGT): Addressing the interoperability bottleneck, we model metadata mapping as a form of bacterial HGT. This allows FDOs to dynamically acquire semantic "traits" (metadata profiles) from heterogenous domains without requiring rigid, centralized schema unification, enabling rapid "non-vertical" evolution of the data space. 3. Bionic Security & Quorum Sensing: We define a digital immune system based on the Major Histocompatibility Complex (MHC) analog, where FDOs utilize cryptographic signatures and RegisterEvent protocols (mimicking Quorum Sensing) to distinguish "self" from "non-self" processes, ensuring data sovereignty and integrity in open, distributed environments. This work provides the architectural blueprint for the next generation of the Internet of FAIR Data and Services, offering a scalable solution for Global Data Spaces, Digital Product Passports (DPP), and autonomous scientific discovery.
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Bin Zhang
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Bin Zhang (Wed,) studied this question.
www.synapsesocial.com/papers/698435b9f1d9ada3c1fb4d13 — DOI: https://doi.org/10.5281/zenodo.18464752