1、 ISO 2016 Data quality Part 100: Master data: Exchange of characteristic data: Overview Qualit des donnes Partie 100: Donnes permanentes: change des donnes caractristiques: Aperu gnral INTERNATIONAL STANDARD ISO 8000-100 First edition 2016-10-01 Reference number ISO 8000-100:2016(E) ISO 8000-100:201
2、6(E)ii ISO 2016 All rights reserved COPYRIGHT PROTECTED DOCUMENT ISO 2016, Published in Switzerland All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or p
3、osting on the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below or ISOs member body in the country of the requester. ISO copyright office Ch. de Blandonnet 8 CP 401 CH-1214 Vernier, Geneva, Switzerland Tel. +41 22 749 01 11 Fa
4、x +41 22 749 09 47 copyrightiso.org www.iso.org ISO 8000-100:2016(E)Foreword iv Introduction v 1 Scope . 1 2 Normative references 1 3 T erms and definitions . 2 4 Abbreviated terms 2 5 Master data . 2 6 Data architecture for master data 4 7 High-level data model . 5 7.1 General . 5 7.2 Diagram . 6 7
5、.3 Entities . 6 7.3.1 data_dictionary 6 7.3.2 data_dictionary_entry 7 7.3.3 data_record . 7 7.3.4 data_set 7 7.3.5 data_object 7 7.3.6 data_object_accuracy_event 8 7.3.7 data_object_completeness_event . 8 7.3.8 data_object_provenance_event 8 7.3.9 property_value_assignment . 8 8 Overview of the mast
6、er data quality series of parts of ISO 8000 . 9 Annex A (normative) Document identification 11 Annex B (informative) Categories of items .12 Bibliography .14 ISO 2016 All rights reserved iii Contents Page ISO 8000-100:2016(E) Foreword ISO (the International Organization for Standardization) is a wor
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12、 specific terms and expressions related to conformit y assessment, as well as information about ISOs adherence to the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see the following URL: www.iso.org/iso/foreword.html. The committee responsible for this document i
13、s Technical Committee ISO/TC 184, Automation systems and integration, Subcommittee SC 4, Industrial data. This first edition of ISO 8000-100 cancels and replaces ISO/TS 8000-100:2009, which has been technically revised. ISO 8000 is organized as a series of parts, each published separately. The struc
14、ture of ISO 8000 is described in ISO/TS 8000-1. Each part of ISO 8000 is a member of one of the following series: general data quality, master data quality, transactional data quality, and product data quality. This part of ISO 8000 is a member of the master data quality series. A list of all parts
15、in the ISO 8000 series can be found on the ISO website.iv ISO 2016 All rights reserved ISO 8000-100:2016(E) Introduction The ability to create, collect, store, maintain, transfer, process and present data to support business processes in a timely and cost effective manner requires both an understand
16、ing of the characteristics of the data that determine its quality, and an ability to measure, manage and report on data quality. ISO 8000 defines characteristics that can be tested by any organization in the data supply chain to objectively determine conformance of the data to ISO 8000. ISO 8000 pro
17、vides frameworks for improving data quality for specific kinds of data. The frameworks can be used independently or in conjunction with quality management systems. ISO 8000 covers industrial data quality characteristics throughout the product life cycle from conception to disposal. ISO 8000 addresse
18、s specific kinds of data including, but not limited to, master data, transaction data, and product data. The master data quality series of parts of ISO 8000 addresses the quality of master data. This part of ISO 8000 is an introduction to the series. It contains an introduction to master data, a dat
19、a architecture, a high-level data model, and an overview of the remaining parts of the series. Annex A contains an identifier that unambiguously identifies this part of ISO 8000 in an open information system. Annex B describes different categories of items and their identifiers. ISO 2016 All rights
20、reserved v Data quality Part 100: Master data: Exchange of characteristic data: Overview 1 Scope This part of ISO 8000 contains an overview of the master data quality series of parts of ISO 8000, which addresses master data quality. The following are within the scope of the master data quality serie
21、s of parts of ISO 8000: master data-specific aspects of quality management systems; master data quality metrics. The approach of the master data quality series of parts of ISO 8000 is to address data quality: from the bottom up, i.e. from the smallest meaningful element, the property value; at the i
22、nterface of master data management systems, not within the systems. The master data quality series of parts of ISO 8000 contains requirements that can be checked by computer for the exchange, between organizations and systems, of master data that consists of characteristic data. These parts address
23、the quality of property values that are exchanged within master data messages. This part of ISO 8000 describes fundamentals of master data quality and specifies requirements on both data and organizations to enable master data quality. The following are within the scope of this part of ISO 8000: spe
24、cification of the scope of the master data quality series of parts of ISO 8000; introduction to master data; description of the data architecture; overview of the content of the other parts of the series. The following are outside the scope of this part of ISO 8000: aspects of data quality that appl
25、y to all data regardless of whether they are master data; aspects of data quality that apply to data that are not master data. EXAMPLE Transaction data are not considered to be master data. 2 Normative references The following referenced documents are indispensable for the application of this docume
26、nt. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any amendments) applies. ISO 8000-2, Data quality Part 2: Vocabulary INTERNATIONAL ST ANDARD ISO 8000-100:2016(E) ISO 2016 All rights reserved 1 ISO 8000-100:201
27、6(E) 3 T erms a nd definiti ons For the purposes of this document, the terms and definitions given in ISO 8000-2 apply. 4 Abbreviated terms MDR master data record UML Unified Modeling Language 5 Master data Within an organization, master data is used to identify and describe things that are signific
28、ant to the organization. NOTE 1 In cataloguing applications, master data are used to describe things called “items”. Figure 1 depicts a taxonomy of data, showing where master data fits. NOTE 2 Figure 1 is not intended to be a complete taxonomy of data; it is only intended to show the context of mast
29、er data. Figure 1 Taxonomy of data (for master data) Master data is typically referenced in business transactions through an identifier. The identifier is commonly a reference both to the thing itself and to a master data record (MDR) that describes the thing. The MDR is commonly held in a central r
30、epository. EXAMPLE 1 It is common for the central repository of MDRs for an organization to be the organizations enterprise resource planning (ERP) or master data management (MDM) system. NOTE 3 What is logically a single MDR can be represented by several physical records in a software system. EXAMP
31、LE 2 In a relational database implementation, a master data record could consist of rows from several different tables. NOTE 4 A MDR that describes something can be identified via a reference using its identifier. Something can be described by characteristic data, represented by property values. Add
32、itionally, something can be described by descriptive strings or definitions.2 ISO 2016 All rights reserved ISO 8000-100:2016(E) Identifying references are designed to be used as references to master data held by others. EXAMPLE 3 A corporate tax identifier, an individuals national insurance number,
33、and a part number assigned by a manufacturer to an item of production are all examples of identifying references. In order for an identifying reference to be meaningful, it shall be associated with a system of identification. EXAMPLE 4 The organization that issued the identifier can be specified by
34、the metadata, as is common in tax identifiers, but a part number is meaningless if the manufacturer that issued it is not known. A description can be computer interpretable characteristic data, which is typically represented as property values, or human readable text. Some properties are differentia
35、ting. Because of the ease with which they can be processed, numerical or controlled values are most often used as differentiating. One of the key aspects of managing master data quality is managing duplication. A consistent approach to managing and eliminating inappropriate duplication is a critical
36、 part of master data management. A characteristic that is considered differentiating by one organization could be considered non- differentiating by another organization. EXAMPLE 5 A manufacturer would have a different master data record for each of its items of production. When, from a buyers persp
37、ective, several items of production (produced by the same manufacturer or different manufacturers) share the same characteristics of fit, form and function, the buyer may group under a single item of supply and assign a “stock number” as the identifying reference for the item of supply. In grouping
38、several items of production as a single item of supply, the buyer is making a decision to consider as non-differentiating one or more characteristics that the manufacturer(s) consider differentiating. A characteristic that is considered differentiating by one function within an organization may be c
39、onsidered non-differentiating by another function within the same organization. Master data is not necessarily static. Also, the number of characteristics needed to describe something will vary by business function. As the number of differentiating characteristics various, MDRs may have to be differ
40、entiated when characteristics are added or changed to differentiating. MDRs may become duplicates when characteristics are removed or changed to be non-differentiating. Examples of master data include: vendor master: This typically describes a vendor in term of its location and legal status. Much of
41、 the mandatory data in a vendor master is prescribed by law as it is a common requirement for a company to be able to identify all entities to which it has transferred funds. customer master: This typically describes a customer in terms of a trading entity. At a minimum it will include the contact i
42、nformation necessary to transmit invoices and may contain confidential information such as credit card information. NOTE 5 If personal data are maintained in a customer master, it can be subject to data protection legislation. item or material master: These masters typically describe tangible items
43、that are tracked, inventoried or regularly purchased. While they are often restricted to items purchased under contract such as production materials they can also be used to improve the quality of spend analysis associated with maintenance, repair and operations (MRO) purchases. Material masters are
44、 also commonly used to support bills of materials (BOM) or to in design where they may be referred to as common parts catalogue or a preferred part list. A variation of the material master is an illustrated parts catalogue (IPC) or a spare parts list. item of supply concept: These masters include a
45、reference to an item or material master, plus packaging and quantity information; service, procedure or process master: These masters are still relatively rare except in the health care and vehicle repair industries where automated billing for services or insurance reimbursement is common. Typically
46、 a service is best described as a procedure or a process. ISO 2016 All rights reserved 3 ISO 8000-100:2016(E) EXAMPLE 6 The American Medical Associations Current Procedural Terminology-4 (CPT-4) codes is an example of a procedure master. asset master: These masters are commonly used to track items w
47、hose purchase price is over a preset monetary value, or whose cost is depreciated over several years. Assets are commonly associated with a unique identifier (serial number) and often associated with movable items where date (time occasionally) and location need to be verified and reported. Correct
48、modelling of an asset master is important to be able to track not only the location and value of the asset over time but also the maintenance and repair activity. A typical problem with asset management is changing specifications over the assets life span. Deciding at what stage an asset has been so
49、 modified as to require the creation of a newly described asset is often a challenging issue. location master: Other than delivery services it is rare to see a separate location master, yet separating out the location master from customer and vendor masters typically leads to improved data quality. The data model for a location master is basically simple as in theory it describes a physical location where global positioning coordinates provide the absolute reference. In practice there may need to includ
