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Standards Database

Find information on AI-related standards using the search and filtering capabilities below. This database currently covers nearly 300 relevant standards that are being developed or have been published by a range of prominent Standards Development Organisations.

Hover over the filter categories here to learn more about them:

Domain The industry or sector that the standard covers (e.g. Energy).

Type of standard Whether the standard covers terminology, processes, performance requirements or measurement requirements.
Application The type of technology, method or application covered by the standard. (E.g. Natural language processing)

Stage of development If the standards is pre-draft, draft or published.
Scope Whether the standard is focused entirely on AI, or is adjacent to AI.

Issuing body The standards body or organisation that issued the standard.
Topic The theme, principle or area covered by the standard (e.g. bias and discrimination).

Committee The standards committee that developed this standard.
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This standard specifies the collaboration protocols of enabling machine learning on the edge computing node with support from industrial clouds. This standard provides implementation reference of machine learning upon lower powered, cheaper, embedded devices, a specific hardware-based method of accepting…
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Standards Body: IEEE
Last updated: 7 Jan 2025
What is ISO/IEC 19944‑1 about? ISO/IEC 19944‑1 is the first part of the multi-series standard that extends the existing cloud computing vocabulary and reference architecture in ISO/IEC 17788 and ISO/IEC 17789 to describe an ecosystem involving devices using cloud services.…
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The standardized ability to categorize data, describe uses of data and apply other facets is useful in several scenarios including the application of policy to data and in describing the use of data to stakeholders. ISO/IEC 19944-1 provides a data…
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This Recommendation provides system context, functional requirements and use cases for machine learning as a service (MLaaS). In particular, the scope of this Recommendation includes: – an overview of machine learning (ML); – an introduction to MLaaS; – functional requirements…
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Standards Body: ITU
Last updated: 7 Jan 2025
What is ISO 23257 – Architecture for Distributed Ledger Technology about? ISO 23257 discusses blockchain and distributed ledger technologies. Ledger technologies is a digital system for recording the transaction of assets in which the transactions and their details are recorded…
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Standards Body: ISO, BSI
Last updated: 7 Jan 2025
This document provides guiding principles and a framework for the governance of DLT systems. The document also provides guidance on the fulfilment of governance, including risk and regulatory contexts, that supports the effective, efficient, and acceptable use of DLT systems.…
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Standards Body: ISO, BSI
Last updated: 7 Jan 2025
This part of BS 10102 provides guidance on good practice for implementing data-intensive projects to realize value, including: a) defining project objectives and project type; b) data project management methodology; c) project roles and responsibilities; d) defining the approach to…
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Standards Body: BSI
Last updated: 7 Jan 2025
This part of BS 10102 gives guidance on realizing value from data, including big data, such as gaining insights, informing strategies, enhancing reputation, and improving compliance, efficiency and performance. To achieve this, guidance is given on managing data efficiently, responsibly…
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Standards Body: BSI
Last updated: 7 Jan 2025
Compared with the traditional network, Recommendation ITU-T Y.3656 can provide better integration and more intelligent capabilities, such as the capabilities of self-optimization, self-configuration, and intelligent fault management, based on big data plane and its machine learning capabilities. This Recommendation can…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T Y.3654 specifies the mechanisms of machine learning in big data driven networking (bDDN). A set of related aspects of machine learning in bDDN are presented, these aspects include: overview, learning procedure, deployment, interfaces, learning path and control path,…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T Y.3603 describes the general concept of metadata and its utilization in a big data ecosystem. Also, this Recommendation provides requirements and a conceptual model of metadata for the data catalogue as well as the extensible markup language (XML)…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU‑T Y.3602 describes a model and operations for big data provenance. This Recommendation also provides the functional requirements for a big data service provider (BDSP) to manage big data provenance. The reliability of data is an important factor in…
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Standards Body: ITU
Last updated: 7 Jan 2025
This document specifies a framework for verifying and validating the interoperability of manufacturing capability units (MCUs) having a set of capabilities that meet the functional requirements of a target manufacturing application solution. The verification and validation framework describes the use…
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Standards Body: ISO, BSI
Last updated: 7 Jan 2025