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The Importance of Data Classification and Structure As the construction and property sectors continue to develop and embrace new technologies including digital twins, cognitive buildings, artificial intelligence and machine learning, there is a need to ensure that data systems are suitable to maximise the potential value and return on investment. Common considerations for data systems include:
+ Scalability: To allow the system to grow. + Flexibility: To allow the system to adapt to changing organisational needs.
+ Granularity: To the level of detail needed to support required functionality.
+ Maintainability: To allow for ease of updates. + Security: To protect sensitive data. Data is at the core of any information system. For a system to be fully useful it is vital the data is structured and named consistently at all building life cycle stages, from design and new construction, into the operation of existing facilities; and through on-going lifecycle upgrades. Not planning for consistent and standardised data structures will cause functionality limitations that can have significant missed opportunity and cost implications. US studies have placed the cost of fragmented data and inadequate interoperability to cost industry in excess of $15.8 billion USD per year. As the complexity of buildings and the capability of digital platforms increase, both the lost opportunity and cost caused by data inconsistency also increases. Many available classification standards are inadequate, overly complex or functionally disjointed to effectively support detailed design, manufacture, construction, commissioning and operational management functionality of the systems that provide ventilation, air conditioning, energy, communications and light to buildings.
+ AS ISO 55000 suite of Standards for Asset Management – The core principle of this suite of standards is that asset management systems facilitate “actions that enable realisation of value from assets”.
In principle, these standards require classification systems to be assigned to classes of objects that enables the naming and analysis of assets and facilitate their management. It’s a process that consists of grouping objects that have similar characteristics or behaviours. And, in order to analyse assets there is a requirement to be able to consistently and reliably identify and group the asset records by type to varying levels of detail, and be able to do this across different types of asset databases. Due to the complexity and requirements of assets at different lifecycle stages and their differing operational requirements, a single classification standard may not enough to serve the various needs thought out a building’s life cycle or an asset life. A constructor’s requirement for classification in a Building Information Model may be different to what is required for an analytics system supporting operation.
Key considerations when looking to adopt a standard include:
+ Fit for purpose – Understanding what outcome is desired from
classification. This can include design, procurement, manufacture, installation, maintenance planning, lifecycle analysis, risk mitigation, energy and performance monitoring.
+ Alignment with international and government standards –
Does the classification system align with existing standards such as ISO 12006 or AS ISO 55000.
International construction and asset management standards provide frameworks to help address these challenges. Commonly referenced standards include:
+ Open and interoperable – Can different classification systems and
+ ISO 12006-2:2015 Building Construction – Organisation of
+ Supported – Is the classification structure supported and
information about construction works which defines a framework for the development of built environment classification systems.
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software products work together, enriching the overall asset data model and not limiting it. regularly updated.
+ Structured and consistent – Is the classification structure logical and consistent across the standard.
Bringing Buildings to Life
Published Oct 2023. While every effort has been made to ensure the accuracy of information in this publication, the A.G. Coombs Group assumes no responsibility for errors or omissions for any consequence of reliance on this publication.