Foreword

ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bodies). The work of preparing International Standards is normally carried out through ISO technical committees. Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee. International organizations, governmental and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization.

The procedures used to develop this document and those intended for its further maintenance are described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types of ISO documents should be noted. This document was drafted in accordance with the editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).

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For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions related to conformity assessment, as well as information about ISO’s adherence to the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see www.iso.org/iso/foreword.html.

This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration, Subcommittee SC 4, Industrial data.

A list of all parts in the ISO 8000 series can be found on the ISO website.

Any feedback or questions on this document should be directed to the user’s national standards body. A complete listing of these bodies can be found at www.iso.org/members.html.

Introduction

0.1 Foundations of the ISO 8000 series

Digital data deliver value by enhancing all aspects of organizational performance including:

operational effectiveness and efficiency;
safety and security;
reputation with customers and the wider public;
compliance with statutory regulations;
innovation;
consumer costs, revenues and stock prices.

In addition, many organizations are now addressing these considerations with reference to the United Nations Sustainable Development Goals1 .

The influence on performance originates from data being the formalized representation of information2 . This information enables organizations to make reliable decisions. This decision making can be performed by human beings directly and also by automated data processing including artificial intelligence systems.

Through widespread adoption of digital computing and associated communication technologies, organizations become dependent on digital data. This dependency amplifies the negative consequences of lack of quality in these data. These consequences are the decrease of organizational performance.

The biggest impact of digital data comes from two key factors:

the data having a structure that reflects the nature of the subject matter;

EXAMPLE 1 A research scientist writes a report using a software application for word processing. This report includes a table that uses a clear, logical layout to show results from an experiment. These results indicate how material properties vary with temperature. The report is read by a designer, who uses the results to create a product that works in a range of different operating temperatures.

the data being computer processable (machine readable) rather than just being for a person to read and understand.

EXAMPLE 2 A research scientist uses a database system to store the results of experiments on a material. This system controls the format of different values in the data set. The system generates an output file of digital data. This file is processed by a software application for engineering analysis. The application determines the optimum geometry when using the material to make a product.

ISO 9000 explains that quality is not an abstract concept of absolute perfection. Quality is the conformance of characteristics to requirements. This means that any item of data can be of high quality for one purpose but not for a different purpose. The quality is different because the requirements are different between the two purposes.

EXAMPLE 3 Time data are processed by calendar applications and also by control systems for propulsion units on spacecraft. These data include start times for meetings in a calendar application and activation times in a control system. These start times require less precision than the activation times.

The nature of digital data is fundamental to establishing requirements that are relevant to the specific decisions that are made by each organization.

EXAMPLE 4 ISO 8000-1 identifies that data have syntactic (format), semantic (meaning) and pragmatic (usefulness) characteristics.

To support the delivery of high‑quality data, the ISO 8000 series addresses:

data governance, data quality management and maturity assessment;

EXAMPLE 5 ISO 8000-61 specifies a process reference model for data quality management.

creating and applying requirements for data and information;

EXAMPLE 6 ISO 8000-110 specifies how to exchange characteristic data that are master data.

monitoring and measuring information and data quality;

EXAMPLE 7 ISO 8000-8 specifies approaches to measuring information and data quality.

improving data and, consequently, information quality;

EXAMPLE 8 ISO/TS 8000-81 specifies an approach to data profiling, which identifies opportunities to improve data quality.

issues that are specific to the type of content in a data set.

EXAMPLE 9 ISO/TS 8000-311 specifies how to address quality considerations for product shape data.

Data quality management covers all aspects of data processing, including creating, collecting, storing, maintaining, transferring, exploiting and presenting data to deliver information.

Effective data quality management is systemic and systematic, requiring an understanding of the root causes of data quality issues. This understanding is the basis for not just correcting existing nonconformities but for also implementing solutions that prevent future reoccurrence of those nonconformities.

EXAMPLE 10 If a data set includes dates in multiple formats including “yyyy‑mm‑dd”, “mm‑dd‑yy” and “dd‑mm‑yy”, then data cleansing can correct the consistency of the values. Such cleansing requires additional information, however, to resolve ambiguous entries (such as, “04‑05‑20”). The cleansing also cannot address any process issues and people issues, including training, that have caused the inconsistency.

0.2 Role of this document

As a contribution to this overall capability of the ISO 8000 series and a specific application of ISO 8000-115 to solve a current problem in the transport exchange, this document specifies requirements for a transport unit identifier (TUID) also referred to as a load identifier. These requirements support the data to represent unambiguously the information that organizations use. Transport unit identifiers are important to organizations because these identifiers allow them to unambiguously identify a load throughout its shipment phases. The transport unit identifier allows systems and software to leverage it to reference, track, describe and record both prospective and actual shipments. This will make it easier to create digitized, value-added activities and services, as well as increase efficiency and effectiveness, for the negotiation process

A shipment life cycle has two major phases. The physical transport phase is generally familiar and well-understood; this phase includes when the carrier is booked and load built (typically when a load identifier is first given), the transport unit is loaded and en route, delivery, and all payments are settled. There are many formal characteristics that are currently standardized and automatable once a load is prepared for shipping, or a carrier is booked. They allow industry procedures and software to know and track each load as it makes its journey.

Before a transport unit (load) is built and the carrier is booked, industry participants often engage in complex negotiations to match loads and carriers, including the decision to source and ship and then carriers are solicited (a formal, industry-wide load identifier is needed by at latest this stage), and they respond. These may encompass familiar and new parties across the industry, especially if the shipper elects to explore the spot market. The negotiation phase relies predominantly on human-centric procedures and systems.

To bring modern digital procedures and systems to facilitate open negotiation including preventing carriers from unknowingly wasting time and resources reviewing and bidding on loads that have already been booked with another carrier, potential loads must be identified and labelled while they are still in the negotiation stage.

Organizations can use this document on its own or in conjunction with other parts of the ISO 8000 series .

This document supports activities that affect:

one or more information systems;
data flows within the organization and with external organizations;
any phase of the data life cycle.

0.3 Benefits of the ISO 8000 series

By implementing parts of the ISO 8000 series to improve organizational performance, an organization achieves the following benefits:

objective validation of the foundations for digital transformation of the organization;
a sustainable basis for data in digital form becoming a fundamental asset class the organization relies on to deliver value;
securing evidence‑based trust from other parties (including supply chain partners and regulators) about the repeatability and reliability of data and information processing in the organization;
portability of data with resulting protection against loss of intellectual property and reusability across the organization and applications;
effective and efficient interoperability between all parties in a supply chain to achieve traceability of data back to original sources;
readiness to acquire or supply services where the other party expects to work with common understanding of explicit data requirements.

ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series .

ISO 8000-2 3 specifies the single, common vocabulary for the ISO 8000 series . This vocabulary is ideal reading material by which to understand the overall subject matter of data quality. ISO 8000-2 presents the vocabulary structured by a series of topic areas (for example, terms relating to quality and terms relating to data and information).

ISO has identified ISO 8000-1 , ISO 8000-2 and ISO 8000-8 as horizontal deliverables4 .

Annex A of this document contains an identifier that conforms to ISO/IEC 8824-1 . The identifier unambiguously identifies this document in an open information system.

1 Scope

This document specifies the requirements for transport unit identifiers (TUID). These requirements supplement those of ISO 8000-115 .

The following are within the scope of this document:

the methods used to identify the originator of a potential shipment;
the methods used to identify the origin and destination locations of a potential shipment;
the requirements for the representation of the originator, origin, and destination locations of a potential shipment in a single identifier.

The following are outside the scope of this document:

the methods used to identify shipments in the transport phase;
the identification of the goods movement phase.

2 Normative references

3 Terms and definitions

4 Fundamental principles and assumptions

5 Encoding a transport unit identifier

5.1 Prefix

5.2 Date and time

5.3 Natural location identifier for transport unit origin

5.4 Natural location identifier for transport unit destination

5.5 Purchase order number formatted as an identifier

6 Requirements for transport unit identifiers

7 Conformance

Bibliography