ISO/IEC

Defines quality criteria

→ Functionality: Correct-ness, appropriateness, completeness

→ Reliability: Maturity, fault tolerance, recoverability

→Usability: Understandabil-ity, operability, learnability, robustness

→Efficiency: economic efficiency, behaviour over time, consumption pattern

→Maintainability: Analysa-bility, modifiability, stability, testability

→Portability: Adaptability, installability, conformity, replaceability

→Security: integrity, confidentiality, authenticity, accountability, non-repudiation

→Compatibility: interoperability (can be used to draw up the specification and test cases

La serie ISO/IEC 25000 è stata sviluppata dall'ISO/IEC JTC1 SC7 Working Group WG6 "Software product and system quality". La prima riunione del WG6 si svolse a Torino nel 1991, anno di pubblicazione dell'ISO/IEC 9126-1, standard precursore dell'ISO/IEC 25010 che dal 2011 lo sostituisce.

L'ISO/IEC 25000 è "estensibile" ed applicabile a vari domini e tendenzialmente "user friendly". Inoltre nel campo delle nuove tecnologie si sta valutando dal 2020 l'estensione dei modelli di qualità nel campo dell'intelligenza artificiale.

ISO/IEC TR 20547-5:2018 describes big data relevant standards, both in existence and under development, along with priorities for future big data standards development based on gap analysis.

This document specifies the big data reference architecture (BDRA). The reference architecture includes concepts and architectural views.

The reference architecture specified in this document defines two architectural viewpoints:

— a user view defining roles/sub-roles, their relationships, and types of activities within a big data ecosystem;

— a functional view defining the architectural layers and the classes of functional components within those layers that implement the activities of the roles/sub-roles within the user view.

The BDRA is intended to:

— provide a common language for the various stakeholders;

— encourage adherence to common standards, specifications, and patterns;

— provide consistency of implementation of technology to solve similar problem sets;

— facilitate the understanding of the operational intricacies in big data;

— illustrate and understand the various big data components, processes, and systems, in the context of an overall big data conceptual model;

— provide a technical reference for government departments, agencies and other consumers to understand, discuss, categorize and compare big data solutions; and

— facilitate the analysis of candidate standards for interoperability, portability, reusability, and extendibility.

SO/IEC TR 20547-2:2018 provides examples of big data use cases with application domains and technical considerations derived from the contributed use cases.

This document describes the framework of the big data reference architecture and the process for how a user of the document can apply it to their particular problem domain.

This document provides a set of terms and definitions needed to promote improved communication and understanding of this area. It provides a terminological foundation for big data-related standards.

This document provides a conceptual overview of the field of big data, its relationship to other technical areas and standards efforts, and the concepts ascribed to big data that are not new to big data

ISO/IEC 18045:2008 is a companion document to ISO/IEC 15408, Information technology - Security techniques - Evaluation criteria for IT security. ISO/IEC 18045:2008 defines the minimum actions to be performed by an evaluator in order to conduct an ISO/IEC 15408 evaluation, using the criteria and evaluation evidence defined in ISO/IEC 15408. ISO/IEC 18045:2008 does not define evaluator actions for certain high assurance ISO/IEC 15408 components, where there is as yet no generally agreed guidance.

Software quality: Quality assessment for AI-based systems (see also 4.1.1 and 4.3.1.4)

Assessment of AI systems: Metrics for the performance capability of AI

Standards for data management within and among local and distributed information systems environments. SC 32 provides enabling technologies to promote harmonization of data management facilities across sector-specific areas. Specifically, SC 32 standards include:

• reference models and frameworks for the coordination of existing and emerging standards;
• definition of data domains, data types, and data structures, and their associated semantics;
• languages, services, and protocols for persistent storage, concurrent access, concurrent update, and interchange of data;
• methods, languages, services, and protocols to structure, organize, and register metadata and other information resources associated with sharing and interoperability, including electronic commerce

Standardization in the area of Internet of Things and Digital Twin, including their related technologies.

1. Serve as the focus and proponent for JTC 1's standardization programme on the Internet of Things and Digital Twin, including their related technologies;
2. Provide guidance to JTC 1, IEC, ISO and other entities developing Internet of Things and Digital Twin related applications;