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# System prepended metadata

title: types of claims & evidence for assuring gemini principles in digital twins

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# Assuring Gemini principles
![image](https://hackmd.io/_uploads/S1VbNkfHa.png)

## Gemini Principle "Function": Federation, Curation & Evolution
**Objective 1 Federation**: To create a digital twin environment that is standard, collective, and connected, enabling secure and resilient data sharing across different systems, sectors, and scales.
**Objective 2 Evolution**: To ensure that the DT is capable of adapting and evolving in response to changes in technology, society, requirements, information management, cybersecurity, data science, and the built environment, while remaining usable and relevant.
**Objective 3 Curation**: To establish clear ownership, governance, and regulation of all aspects of the NDT, ensuring accountability for high-quality data management and adherence to standards across the ecosystem.

_The following claims and evidence are collected based on a case study of the CreDo, specifically the published [technical report](https://digitaltwinhub.co.uk/files/file/121-credo-technical-report-1-building-a-cross-sector-digital-twin/)_

- **E1: Standard & Open Data Formats**
    - Use of universally accepted or widely recognized data formats (e.g., JSON, GeoJSON).
    - **Architecture Level**: Data ingress & management
- **E2: Integrated Infrastructure Database**
    - **Evidence Specification**: Utilization of a centralized or integrated database system that combines and analyzes datasets from various sources.
    - **Architecture Level**: Data ingress & management
- **E3: Extensible & Open Data Querying Protocol**
    - Use of flexible, standardized querying protocols like SPARQL that can handle diverse and distributed datasets.
    -  Adoption of open standards and protocols that are not tied to specific vendors or technologies facilitates evolution of DT in the future
    - **Architecture Level**: Data ingress & management
- **E4: Simplified and Abstract Data Representations**
    - Implementation of hierarchical ontologies or similar structures that simplify and abstract complex data.
    - **Architecture Level**: Modeling & Simulation
- **E5: Representation of Cross-Sector Dependencies**
    - Ability to model and represent complex interactions and dependencies across different sectors.
    - **Architecture Level**: Modeling & Simulation
- **E6: Extensible Dashboard or Interface**
    -Capability to incorporate various data types and formats, demonstrating adaptability and extensibility.
    - **Architecture Level**: User interface and visualization layer.
- E7: **Secure Data handling is ensured through DAFNI**
    - The project's use of DAFNI's National Infrastructure Database for combining and analyzing datasets implies a level of security in data handling.
    - DAFNI provides the necessary technical infrastructure, skilled IT staff, legal agreements, and security credentials for this purpose.
    - **Architecture Level**: Data ingress & management
- E8: **Vizualisation use is secure**
    - Keycloak is used by vizualisation to obtain an authentication token to retrieve and display simulations
    - **Architecture Level**: User interface and visualization layer.
- E9: **Continuous Integration/Continuous Deployment (CI/CD) Practices**
    - Argo and Kubernetes offer features like container isolation, controlled resource access, and secure networking, which are essential for protecting data during processing and transfer.
    - Containerisation enables the creation of modular components in the digital twin project, allowing for independent development, deployment, and management, thereby facilitating easy updates and scalability for system adaptability and evolution.
    - **Architecture Level**: Data ingress & management
- E10: **Multi-Factor Authentication (MFA) Solution is implemented**
    - Developed by STFC, this solution provides security and access controls, handling both authentication (confirming user identity) and authorization (controlling user access to specific nodes).
    - **Architecture Level**: User interface and visualization layer.
- E11: **Regular Security Updates and Audits**
    - Regular updates and audits to address evolving cybersecurity threats and vulnerabilities.
    - **Architecture Level**: Security & compliance
- **E12: Extensible and Adaptable Ontologies**
    - Implementation of a core asset ontology and sub-domain ontologies, designed to be extensible and adaptable for future phases.
    - **Architecture Level**: Modeling & Simulation
- **E13: Flexible Data Ingestion and Mapping**

    - **Evidence Specification**: Use of Ontop for mapping asset owner data to the CreDo ontologies, allowing integration of various data formats.
    - **Architecture Level**: Data ingress & management
- **E14: Synthetic Data for Safe Testing and Evolution**
    - **Evidence Specification**: Creation of synthetic asset data to support dissemination and testing without compromising confidentiality.
    - **Architecture Level**: Data processing & testing
- **E15: Trusted Third Party and Independent Operator**
    - **Evidence Specification**: DAFNI's role as a trusted third party and independent operator, crucial for managing sensitive datasets.
    - **Architecture Level**: governance
- **E16: National Infrastructure Database**
    - **Evidence Specification**: Utilization of DAFNI's National Infrastructure Database for secure data combination, analysis, and destruction post-project.
    - **Architecture Level**: governance
- E17: **Architecture is distributed**
    - Distributed knowledge graph across multiple servers, enhancing interoperability and data governance.

Data governance more widely:
1. **Data Collection Standards**
2. **Access Control**
3. **Compliance with Regulations**
4. **Data Quality Assurance**
5. **Data Usage Policies**
6. **Data Security Measures**

## Other gemini principles

1. **Security**:
    
    - **Trusted Third Party and Independent Operator**: DAFNI's role as a trusted third party and independent operator is crucial for ensuring secure data handling.
    - **Multi-Factor Authentication (MFA) Solution**: Developed by STFC, this solution enhances security by confirming user identity and controlling access to specific nodes.
2. **Openness**:
    
    - **Interoperability and Knowledge Graph**: The distributed knowledge graph across multiple servers enhances interoperability, aligning with open standards.
    - **Data Mapping with Ontop**: This allows for integration of various data formats into the CreDo data structure, promoting openness and compatibility with other data models.
3. **Quality**:
    
    - **National Infrastructure Database**: Utilizing DAFNI's database for combining and analyzing datasets ensures data quality and accuracy.
    - **Sensitive Data Handling**: The technical infrastructure, skilled IT staff, and legal agreements in place ensure the quality and integrity of sensitive data.
4. **Public Good**:
    
    - **Synthetic Data**: The creation of synthetic asset data for dissemination respects confidentiality while serving the public interest by providing valuable insights without compromising real data.
    - **Information Cascade Model**: This model, which resolves the cascade of effects caused by asset failures, is crucial for modeling scenarios that have significant implications for public infrastructure and safety.
5. **Value Creation**:
    
    - **Workflow Schematic and Data Ingestion**: The dynamic workflow with a time loop and the integration of various models demonstrate the potential for innovation in data processing and analysis.
    - **Visualization Features**: The digital twin's visualization tool, which displays assets and their operational states, fosters understanding and innovation by making complex data accessible and interpretable.