This part of BS 10102 gives guidance on realizing value from data, including big data, such as gaining insights, informing…
Process, management and governance
This part of BS 10102 provides guidance on good practice for implementing data-intensive projects to realize value, including: a) defining…
Recommendation ITU-T Y.3654 specifies the mechanisms of machine learning in big data driven networking (bDDN). A set of related aspects…
What is PAS 1881:2022 about? PAS 1881:2022 is the first full revision of PAS 1881:2020 to reflect learning from recent…
Recommendation ITU‑T Y.3602 describes a model and operations for big data provenance. This Recommendation also provides the functional requirements for…
This document reviews current aerospace software, hardware, and system development standards used in the certification/approval process of safety-critical airborne and…
New broadcasting technologies driven by artificial intelligence (AI) are being introduced to the broadcasting workflow. These technologies are intended to…
This document provides guidelines for evaluation of AI systems using an AI system quality model. The document is applicable to…
This DIN SPEC has been developed within a DIN SPEC consortium. The document was developed and approved by organizations named…
Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 1: Quality Meta Model
This DIN SPEC in accordance with the PAS procedure has been drawn up by a DIN SPEC (PAS)-consortium set up…
This document provides a data quality governance framework for analytics and machine learning to enable governing bodies of organizations to…
