City Scape

Using Ontology to Refine and Unify Asset Information and Solve Your Most Intractable Data Problems

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Original date: 
Wednesday, September 13, 2023

Information ontologies have been used to integrate information and clarifying the meaning of its contents in the biomedical domain for decades. More recently, the approach is seeing wider adoption in the financial services and industrial domain. In this presentation, we address three familiar problems commonly observed in all industrial sectors. The first is the undesirable state of having multiple sets of information about the same assets stored in independent silos. There are many popular solutions to this problem; we contend that they are fragile due to a second problem. The second problem is that asset records in different data sources (e.g., an engineering drawing repository, work management system, or SCADA database) representing the same asset are updated independently. This leads to inconsistencies between the data sources over time. The third problem is the most critical and perhaps the most intractable – the contents in the data contain pernicious ambiguities. As a result, we cannot find in the data the clear and definitive answers to guide asset management decisions. Ontologies, and their utility for disambiguation and semantic integration, are well suited to support these challenges of asset record management. We present an ontology for asset information integration currently being trialed at Toronto Water for the audience to assess.

BoK Content Source: 
MainTrain 2023
BoK Content Type: 
Presentation Slides
Asset Management Framework Subject: 
04 Asset Information, 4.00 Asset Information General, 4.01 Asset Information Strategy, 4.04 Data & Information Management
Maintenance Management Framework Subject: 
09 Information Management, 9.3 Master Data Management
Author Title: 
Author Employer: 
City of Toronto - Metro Hall
Author Bio: 

Tony Huang is a senior engineer at Toronto Water. He specializes in the reliability of electrical equipment and, more recently, data and information management foundations for asset management.

Author 2 Title: 
Author 2 Employer: 
University of Toronto
Author 2 Bio: 
Dr. Megan Katsumi is a research associate at the University of Toronto.