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May 12, 2026Construction Innovation0 citations

A semantically structured relational database for construction safety analysis

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MNMirza Muntasir NishatPNPeder Solem NervikNONils O.E. Olsson

Key Points

  • This research aims to develop a structured database to enhance safety analysis and decision-making in construction projects.
  • Developed a normalized relational database with structured relationships from a dataset of a Norwegian construction firm's records.
  • Included data on accidents, events, observations, and quality deviations.
  • Created queries to evaluate safety performance based on the organized data.
  • The database provided comprehensive information on accidents, projects, stakeholders, and associated risks.
  • Identified constraints such as nonoverlapping identification numbers, time differences, and lack of risk factors affecting detailed analysis.
  • Promoted data-driven methods that can enhance safety performance and support future applications of artificial intelligence.

Abstract

Purpose This study aims to provide experiences of a pilot database development to discuss the opportunities for automation of safety in construction. It also explores how organized data can be used to improve safety analysis and decision-making between and inside projects. Design/methodology/approach The data set included the records of construction works carried out by a Norwegian construction firm, which comprised accidents, events, observations and quality deviations. A normalized relational database containing structured relationships between the affected projects was built, and queries were developed to evaluate safety performance. Findings The systematic database contributed to the information on accidents, projects, stakeholders and risks involved with the construction company. Nevertheless, the nonoverlapping identification numbers, time differences and absence of risk contributing factors might constrain a detailed analysis. Practical implications This systematic database seems to be very helpful in automated safety management regarding trend identification and constraint management. This research promotes the application of data-driven methods in construction activity to improve safety performance and introduce the artificial intelligence-based system in the future. Originality/value This pilot research addresses the experiences of developing a structured database for safety performance analysis from the data received from a construction company. Hence, it demonstrates a pilot model that can accommodate various data types, from accident reports to workforce presence, within a common analysis framework, which can play the role of creating a foundation for automation and data-driven predictive analysis in this field.

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Cite This Study

Nishat et al. (2026) studied this question.

synapsesocial.com/papers/6a02c324ce8c8c81e96407cehttps://doi.org/10.1108/ci-06-2025-0259
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