Slide 1

Data Quality Symposium

Data Quality – An International Challenge

Peter R. Benson

2009-04-23

Magaliesburg, South Africa

An Association of

Master Data Quality Managers

EDIElectronic Data Interchange

The

electronic exchange

of

business information

between

computer applications

© Peter Benson 1994

EDIDefines Meaning not Format

An EDI message contains Informationidentified by standard tags and codes

organized in accordance with a standard syntax

EDI data is easy to identify - easy to manipulate

EDI is not SGML!

© Peter Benson 1994

Personalized Publishing

The technology exists to provide customers with accurate, up to date information, on demand, in the form best suited to their needs.

The Value of information is directly proportional to its accuracy, relevance and ease of use.

© Peter Benson 1994

Slide 5

Wisdo

m

Knowledge

Information

meaningful data

Data

a datum is a disruption in a continuum

Slide 6

Data transfers information

the theoretical view

Information

Information

Data

Slide 7

Data transfers informationthe practical view

Data

Information Information

Slide 8

Tackling the problem

Data quality

• Syntax

• Semantic encoding

• Conformance to requirements

Information Information

Pro

cess

Pro

cess

Process

ISO 8000

The International Standard for Data Quality

ISO TC 184 SC 4

Project leader: Peter Benson

Editor: Gerald Radack

Slide 10

ISO TC184 SC4 Industrial data

– ISO 10303 (Product models)

– ISO 22745 (Open technical dictionaries)

– ISO 8000 (Data quality)

– ISO 8000-100 (Master data)

156 National standard

organization members

(one per country)

• 192 Technical Committees

• 3,000 Technical bodies

• 50,000 domain experts

• Central Secretariat in Geneva

• 150 staff

Slide 11

• South Africa, SABS; South African Bureau of Standards

• Spain, AENOR; Asociación Española de Normalización y Certificación

• Sweden, SIS; Swedish Standards Institute

• Switzerland, SNV; Swiss Association for Standardization

• United Kingdom, BSI; British Standards Institution

• United States, ANSI; American National Standards Institute

• Australia, SAI; Standards Australia International, Ltd

• Austria, ON; Österreichisches Normungsinstitut

• Brazil, ABNT; Associação Brasileira de Normas Técnicas

• Bulgaria, BDS; State Agency for Standardization and Metrology

• China, SAC; Standardization Administration of China

• Czech Republic, CNI; Czech Standards Institute

• France, AFNOR; Association française de normalisation

• Germany, DIN; Deutsches Institut für Normung

• Italy, UNI; Italian National Standards Body

• Japan, JISC; Japanese Industrial Standards Committee

• Korea, KATS; Korean Agency for Technology and Standards

• Netherlands, NEN; Nederlands Normalisatie-instituut

• Norway, SN; Standards Norway

• Portugal, IPQ; Instituto Português da Qualidade

• Russia, GOST; Federal Agency on Technical Regulating and Metrology

ISO TC184 SC4

voting members

ISO 8000 - Data quality

• ISO 8000 addresses data quality. ISO 8000 is

concerned with:

• the principles of data quality;

• the characteristics of data that determine its

quality;

• the processes to ensure data quality.

ISO 8000-100 Master data quality

Slide 13

ISO 8000-100: – Master Data Quality

data

transactional data

master datadescribes entities that are independent

and fundamental for the organization;

needs to be referenced in order to

perform transactions

referencing datadefined by reference to

another organization’s

master data

characteristic datadefined by the

characteristics of the entity

being described

Slide 14

• Customers

• Suppliers

• Materials

• Items

• Services

master data

data held by an organization that describes the entities that are both independent and fundamental for an enterprise, that it needs to reference in order to perform its transactions

Master data describes individuals, organizations, locations, goods,

services, rules and regulations.

• Assets

• Locations

• Employees

• Rules

• Regulations

ISO 8000-102

Slide 15

In a business environment data quality must

be measured by the degree to which it

successfully supports a defined business

function

Generic

• Asset visibility

• Financial transparency

• System integration

• System interoperability

• Data portability

Specific• Design

• Manufacturing

• Operations

• Procurement

• Logistics

• Inventory management

• Disposal

Slide 16

• Transparency

– who, what, where, when (4W)

• Data portability

– System interoperability

Quality Datais required

Slide 17

• Across the supply chains

• In design and engineering

applicationsCAD-CAM-CAE

• In ERP/MDM applications Asset, vendor, customer, material, service masters

• In production applicationsPDM

• In product life cycle management

• In asset management applications

• In human resources applications

Common Concept Encoding“metadata”

Customer

Vendor

Human

Resources

Material

Facilities

Production

Slide 18

Terminology mapping

Terminology

Terminology

Terminology

GSA-IAETerminology

IndustryCSC

SDO

SDO

Terminology

• Public domain concept identifiers

• Free identifier resolution to underlying

terminology (web services)

• Hyperlink to source standards

• Multilingual

• Multiple terms, definitions and images

linked to single concept identifier

Slide 19

Automating the data supply chain

Data

requestor

Data

provider

Sub

eOTD-i-xml(data requirements statement) ISO 22745-30

eOTD-q-xml(query)‏

ISO 22745-35

Sub-Tier

eOTD-q-xml

Sub-Tier

eOTD-r-xml

eOTD-r-xml(reply)‏

ISO 22745-40

Faster access – Better quality – Cheaper process

Slide 20

Supplier and Manufacturers recognize that:

- data integration is one of the keys to a long term relationship

- the ability to provide their customers with quality data is a significant differentiating factor.

Suppliers and Manufacturers are:

- publishing the specifications of their products, capabilities and services on their web sites.

- looking to increase their visibility and understand that the best way to do this is to improve the quality of their data.

Promoting adoption

Suppliers and manufacturers are looking for a Standard that they can use to identify the quality of their data.

Slide 21

a. The data shall be ISO 8000-110:2008 compliant.

b. The data shall comply with registered ISO 22745-30 compliant

Identification Guides.

c. The data shall be encoded using concept identifiers from an ISO

22745 compliant open technical dictionary that supports free

resolution to concept definitions.

d. The data shall be provided in an ISO 22745-40 compliant

Extensible Markup Language (xml) format.

The contractor, sub-contractor or supplier shall, as and when requested

to do so, supply technical data in electronic format on any of the items

covered in this contract as follows:

Buyer contract clauseRequiring adoption

Providing the data necessary for the safe and efficient operation of plant and equipment is a legal requirement in most countries

Slide 22

Data quality and Intellectual Property (IP)

All identifiers are copyright. They belong to the organization that issued them and their use is subject to the terms and conditions imposed by the issuer.

Unless identifiers have been declared available for public use without a licence, they should never be used to retrieve data that was not supplied by the owner of the identifier unless you have specific permission to do so.

In order to protect your data from claims of “joint work” you should not use proprietary identifiers as metadata.

is portable data!

Slide 23

Lock in

A common commercial practice

A computer system (1960-1980)

Hardware – software (1980-2005)

Hardware – software – data (2005 -

Standards are the key to avoiding lock in

Legislation is sometimes required

is portable data!

Slide 24

Thank you