since 2010 and represented BCS in the development of a pair of big data-inspired standards developed by the British Standards Institution (BSI). Julian managed projects to develop asset information guidance and demand analysis guidance for the Institute of Asset Management. His standards development work has included the PAS 1192 standards suite for building information modelling (BIM) and their subsequent translation to the ISO 19650 series. He also contributed to ISO 8000, BS 10102-1 (Big data: Guidance on data-driven organizations) and BS 10102-2 (Big data: Guidance on data-intensive projects).
Julian regularly delivers conference presentations on data- and asset-related topics and has chaired a number of data-related conferences.
xi
The authors would like to thank all the people and organisations whose challenges and approaches to data have created the anecdotes and solutions that have inspired much of the content of this book. We gratefully acknowledge the experts who work in ISO/TC184/SC4/WG13 (Industrial Data) and developed ISO 8000-61, which provides the core focus of this book. Data and Process Advantage Limited have allowed reuse of the ‘Data Zoo’ concept to help illustrate the behavioural aspects of data quality. Thank you to Ian Rush for the inspiration behind the ‘Do your data trust you?’ example.
Acknowledgements
xii
BIM building information modelling
BSI British Standards Institution
CDO chief data officer
CIO chief information officer
CTO chief technology officer
DMBOK Data Management Body of Knowledge
EDMS electronic document management system
GDPR General Data Protection Regulation
HUMS health and usage monitoring system
IoT Internet of Things
ISO International Organization for Standardization
IT information technology
JPEG Joint Photographic Experts Group
MDM master data management
NASA National Aeronautics and Space Administration
NHS National Health Service
PAF Postcode Address File
PoD Prophet of Doom
SEP Somebody Else’s Problem
USPS United States Postal Service
ABBREVIATIONS
xiii
Glossary
Accuracy: Agreement between a data item and the entity that it represents. For reference, accuracy should be checked to ensure that: each data item links to a specific entity; each entity has a data entry related to it.
Attribute: Data field used to record the characteristics of an entity. Single unit of data that in a certain context is considered indivisible (ISO/TS 21089:2018).
Chief data officer (CDO): An individual appointed at senior level in an organisation to facilitate the effective specification, acquisition, exploitation and governance of data. CDO also can refer to chief digital officer; however, this role is typically more focused on exploitation of data through digital technology.
Completeness: The quality of having data records stored for all entities and that all attributes for an entity are populated.
Consistency: The ability to correctly link data relating to the same entity across different data sets.
Data: Reinterpretable representation of information in a formalized manner suitable for communication, interpretation or processing (ISO 8000-2:2020).
Data custodian: See Data steward.
Data governance: Development and enforcement of policies related to the management of data (ISO 8000-2:2020).
Data management: The activities of defining, creating, storing, maintaining and providing access to data and associated processes in one or more information systems (ISO/IEC TR 10032:2003).
Data owner: An individual who is accountable for a data asset.
Data quality: Degree to which a set of inherent characteristics of data fulfils requirements (ISO 8000-2:2020).
Data quality criteria: Specific tests that can be applied to data in order to understand the nature of their quality. This can also include the methods to be used in assessing quality.
xiv
Glossary
Data quality management: Coordinated activities to direct and control an organisation with regard to data quality (ISO 8000-2:2020).
Data set: Logically meaningful grouping of data (ISO 8000-2:2020).
Data steward: Person or organisation delegated the responsibility for managing a specific set of data resources (ISO 8000-2:2020).
ISO 8000: The multi-part ISO standard for data quality.
ISO 9000: The family of standards addressing various aspects of quality management, providing guidance and tools for companies and organisations who want to ensure that their products and services consistently meet customers’ requirements, and that quality is consistently improved.
Metadata: Data defining and describing other data (ISO 8000-2:2020).
Precision: Degree of specificity for a data entry (ISO/IEC 11179-3:2013 - modified).
Structured data: In a data set, the meaning covered by explicit elements of the data (e.g. the tables, columns and keys within a relational database or the tags within an XML file).
Timeliness: A measure of how current a data item is.
Uniqueness: A measure of whether an entity has a single data entry relating to it within a data set.
Unstructured data: In a data set, levels of meaning that are not covered by structural elements of the data (e.g. the characteristics of the brain in the image of a diagnostic medical scan).
Validity:
