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Digital Asset Management (DAM) has emerged as an advanced approach to empower asset managers in controlling and optimizing asset operations. This study addresses the challenge of integrating metadata from a repository of 2340 reported asset problems at one of the public schools in Saudi Arabia over 2 years. The data, obtained in .xls format from the existing asset/facility information management system, was meticulously unified to visualize digital assets enriched with relevant data. Findings showed, among others, repeated data/records, incomplete/inaccurate data, language issues, lack of time reporting a problem, absence of status reports, and confusion between asset and facilities data. The primary aim is to explore the integration of this metadata into an Asset Information Model (AIM) for more efficient asset management. The proposed integrated strategy for supporting metadata in AIM analysis emphasizes effective metadata management. By defining metadata requirements, establishing robust standards, implementing efficient capture and storage processes, seamlessly integrating metadata into the AIM model, establishing governance procedures, leveraging metadata in analysis, and continuously monitoring and optimizing the strategy, organizations enhance the accuracy, consistency, and integrity of AIM analysis. This comprehensive approach fosters improved decision-making in asset and facility management, leading to enhanced overall efficiency. Successful implementation and further research on this strategy contribute to AIM analysis advancement and metadata utilization optimization, elevating asset management practices in the evolving construction and infrastructure industry. This research provides valuable insights into digital asset management and presents a compelling blueprint for leveraging metadata integration for effective asset management strategies.
Ahmed Mohammed Alkhard (Thu,) studied this question.