Standard

ISO 13381-1:2015 provides guidance for the development and application of prognosis processes. It is intended to

- allow developers, providers, users and manufacturers to share common concepts of prognostics,

- enable users to determine the data, characteristics, processes and behaviours necessary for accurate prognosis,

- outline appropriate approaches and processes to prognostics development, and

- introduce prognostics concepts in order to facilitate future systems and training.

Other parts will include the introduction of concepts of the following forms of prognostic approaches: performance changes (trending) approaches (ISO 13381-2), cyclic-driven life usage techniques (ISO 13381-3), and useful-life-remaining models (ISO 13381-4).

This document describes the general content and structure of the entire QIF information model. It describes the highest level data structures of QIF, that are expanded in Clauses 6 through 12 using data dictionaries and XML schema files. All QIF XML schema files can be found at www.qifstandards.org.

This document also describes practices for forming QIF instance files, called "documents," that support quality workflow scenarios. Its focus is to show how the QIF information model, and data formed into XML instance files, support the entire scope of model based definition manufacturing quality workflow. It describes how the information model is partitioned among the XML schema files and contains all terms used in the subject area clauses.
The purpose of this document is to orient potential users of QIF to the organization of the information model to make their study of the details more rewarding and efficient. It should also help solution providers and users to evaluate QIF for their uses, without needing to go to the lowest technical details of the XML schemas. The information model narrative focuses on the approach to modeling the core data structures of QIF, which model the content of ASME GD&T and ISO GPS, and the plans and results data elements defined in Dimensional Measuring Interface Standards (DMSI) ISO 22093 and ANSI/DMSC DMIS 5.3. The material on XML practices describes consistent design practices to be used by QIF working groups who will be designing new schemas. It should also help data processing experts to write software that writes and reads manufacturing quality data using the XML schemas.

This document provides principles for IoT trustworthiness based on ISO/IEC 30141 – IoT Reference Architecture.

ISO/IEC TS 33052:2016 defines a process reference model (PRM) for the domain of information security management. The model architecture specifies a process architecture for the domain and comprises a set of processes, with each described in terms of process purpose and outcomes.

This document specifies requirements for an Internet of Things (IoT) data exchange platform
for various services in the technology areas of:
 the middleware components of communication networks allowing the co-existence of IoT
services with legacy services;
 the end-points performance across the communication networks among the IoT and legacy
services;
 the IoT specific functions and functionalities allowing the efficient deployment of IoT
services;
 the IoT service communication networks’ framework and infrastructure; and
 the IoT service implementation guideline for the IoT data exchange platform.

This document specifies a formal logic-based concept specialization approach to support the development of manufacturing reference models that underpin the necessary business specific knowledge models needed to support the configuration of global production networks.

This document specifies the following:

— the formal sematic model approach;

— hierarchical levels for property specialization;

— contexts for each level;

— key properties at each level;

— property relationships;

— property axioms;

— applicability rules.

The following are within the scope of this document:

— production networks for discrete product manufacture;

— formal semantics for the configuration of global production networks;

— system level formal semantics;

— designed system formal semantics;

— manufacturing business system formal semantics;

— global production systems network formal semantics.

The following are outside the scope of this document:

— in-factory formal semantics;

— formal semantics for the operation of global production networks.

SAML is an XML-based framework for exchanging security information. This security information is expressed in the form of assertions about subjects, where a subject is an entity (either human or computer) that has an identity in some security domain. A single assertion might contain several different internal statements about authentication, authorization and attributes. This Recommendation defines a protocol by which clients can request assertions from SAML authorities and get a response from them. This protocol, consisting of XML-based request and response message formats, can be bound to many different underlying communications and transport protocols; SAML currently defines one binding to SOAP over HTTP. In creating their responses, SAML authorities can use various sources of information, such as external policy stores and assertions that were received as input in requests. This Recommendation defines SAML assertions elements, subjects, conditions, processing rules and statements. Additionally, it develops a comprehensive SAML metadata profile that includes associated namespace, common data types, processing rules and signature processing. Several protocol bindings such as SOAP, PAOS (reverse SOAP), HTTP redirect, HTTP POST, among others, are also developed. This Recommendation provides a comprehensive list of SAML profiles such as web browser SSO profile and single logout profile to enable the wide adoption of SAML 2.0 in the industry. Guidelines for authentication context and conformance are also provided.This Recommendation is technically equivalent and compatible with the OASIS SAML 2.0 standard.

This standard specifies the requirements and methods for verifying the identity of a person equipped with human augmentation technologies. Human augmentation, also known as human enhancement, refers to technologies that add to the human body and enhance human productivity or capability. Recent advancements in many technical areas have led to a large variety of implants, wearables and other technologies that could be classified as human augmentation.