Data and compute
Data and compute have become infrastructure: the capacity to train and run models, store and move data and keep them secure is concentrated, energy-intensive and a dependency for science, government and finance.
- Institution
- The Global Centre for Risk and Innovation (GCRI)
- Service level
- R0: information and enquiries
The short answer.
Data and compute as a field of risk covers the data infrastructure and computing capacity that science and public services rely on, with its stewardship, energy, security and concentration risks. In the Nexus Consortium it is studied as science at GCRI by Nexus Foundry as well as Artificial Intelligence and Autonomous Systems; this gateway links those platforms and the methods they share.
The field, seen three ways.
Science and evidence
Nexus Foundry, Artificial Intelligence and Autonomous Systems, Data and Compute
Governance and dialogue
No platform yet in this field.
Financial understanding
No platform yet in this field.
Concentration, energy and sovereignty.
Advanced chips come from a short supply chain; hyperscale capacity sits with a few providers in a few regions; data-centre growth is changing electricity demand forecasts and water use where it clusters. For public institutions the questions are continuity of access, jurisdiction over data, and the energy and water footprint of the services they depend on.
- Power usage effectiveness and water usage effectiveness as site-level metrics.
- Data residency and lawful access across jurisdictions.
- Supply of accelerators and the export-control environment around them.
Metrics and governance.
| Framework or body | What it governs or supplies |
|---|---|
| ISO/IEC 30134 series | Key performance indicators for data centres, including power usage effectiveness |
| FAIR principles | Findable, accessible, interoperable and reusable data |
| NIST CSF 2.0 and ISO/IEC 27001 | Security of compute and data services |
| Global Digital Compact | Intergovernmental commitments on data governance and digital cooperation |
Compute's dependencies and dependants.
- Energy: grid connection and load growth.
- AI: capability tied to compute.
- Water: cooling demand in water-stressed areas.
The science sits on Data and Compute; methods start from computing.
The methods behind the field.
- High-performance, cloud and edge computing
- Data engineering, interoperability and stewardship
- Geospatial information systems
- Artificial intelligence and machine learning
- Systems engineering
- Software and safety-critical systems engineering
- AI evaluation and assurance engineering
- Probability and statistics
- Cybersecurity and cryptography
- Social and behavioural science
- Robotics and automation
- Energy generation, storage and grid technology
- Optimization and operations research
- Physics and quantum science
- Power systems engineering
Terms used on this page.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Digital twin | A computational representation of a physical system that is updated with data from it and used to explore its behaviour. |
| Data infrastructure | The systems, standards and institutions that collect, store, describe, govern and share data. |
| Data pipeline | A sequence of automated steps that ingests, validates, transforms and publishes data. |
| Fail closed | A design in which a control that cannot decide denies the request rather than allowing it. |
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why does GCRI host field gateways?
Around GCRI.
Start with an enquiry.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.