Asoba Ona Documentation

Data Sovereignty

The Principle of Autonomy in the Digital Age

Data sovereignty is the principle that data is subject to the laws and governance structures within the nation or entity where it is collected and processed. It is the right of a country, organization, or individual to control their own data, ensuring that critical information is not subject to foreign access or control. This concept extends beyond national borders, applying to any entity—from a government to a private business—that seeks to maintain ownership and control over its digital assets.

Why Data Sovereignty Matters

For nations, data sovereignty is a matter of national security and economic stability. For private businesses, it is about protecting intellectual property, maintaining a competitive advantage, and ensuring customer trust.

Key Risks of Ceding Data Sovereignty:

The Intelligence Layer: A Framework for Data Sovereignty

The “Intelligence Layer” provides a practical framework for achieving data sovereignty by moving compute to the edge, rather than moving data to centralized data centers. This is achieved through a distributed AI model embedded within critical infrastructure, such as Distributed Energy Resource Management Systems (DERMS).

How it Works:

01
Collect

Edge-Based Perception

Edge-based sensors collect environmental, grid, and asset telemetry in real-time, keeping the data at its source.

02
Predict

Sovereign Prediction

Machine learning models run locally on sovereign datasets, allowing for predictions (e.g., local energy demand, generation, and risk) without exposing the raw data to external entities.

03
Operate

Decentralized Operations

The system enables dynamic dispatch, microgrid reconfiguration, and resilience management at a local level, with each node acting as a cognitive unit.

By embedding intelligence at the edge, the Intelligence Layer creates a resilient and sovereign system. Each node contributes to a live intelligence graph of the energy topology, forming a collective “brain” that can perform decentralized inference while retaining local data sovereignty. This approach allows nations and businesses to participate in the global computational economy on their own terms, without sacrificing control over their most valuable asset: their data.