Introduction
Fire protection systems are an essential part of a building’s safety ecosystem. The installation of such systems is just the beginning of a more dynamic safety process that requires diligent inspection, testing and maintenance (ITM) efforts. ITM plays a significant, fundamental role in managing facility risks, and ensures that systems will activate as intended, when needed, and ultimately minimize downtime — because down time equates to accumulated risk. There are nearly 70 NFPA codes and standards requiring some form of ITM.
In recent years, there has been interest in using inspection, testing, and maintenance activity data to inform decisions related to system reliability, risk acceptability, and ITM frequencies. These data are being captured in thousands of different formats, through hundreds of different approaches, and by thousands of different groups, but one key element has been lacking to date - standardization. This void has restricted the ability to determine sound performance-based inspection frequencies and prevents stakeholders from exchanging and analyzing data that can influence safety and efficiencies.
To address this need, the Fire Protection Research Foundation initiated a project titled “ITM Data Exchange” to develop and pilot test a novel approach to standardizing ITM data using concepts of linked data and graph-modeling. The project developed a proof-of-concept comprehensive, scalable, and extensible ITM data model that can support reliability analyses and predictive analytics. Guided by the concepts of fair data principles, this study demonstrates how graph-modeling and other cutting-edge techniques are being leveraged to collect and consolidate data to enable further analysis, reporting, and sharing of ITM data for the needs of various stakeholder groups.