Smart and Sustainable Reconstruction Enabled by BIM: A Lifecycle Information Governance and Decision Intelligence Framework

Post-disaster reconstruction requires more than the restoration of physical assets. It also depends on maintaining reliable relationships between recovery needs, engineering requirements, information, evidence, intervention decisions, and subsequent lifecycle outcomes. Although existing research provides substantial foundations for post-disaster needs assessment, BIM-enabled delivery, sustainability and resilience evaluation, requirements traceability, decision support, digital twins, and lifecycle monitoring, these capabilities are frequently addressed through different disciplinary and governance structures. This conceptual working paper develops a BIM-enabled lifecycle information governance and decision intelligence framework for smart and sustainable reconstruction. The framework connects disaster impacts and recovery needs with reconstruction requirements, information requirements, governed information, decision-relevant evidence, engineering assessment, accountable human and institutional decisions, reconstruction interventions, lifecycle outcomes, requirement verification and reassessment, recovery-need outcome assessment, and lifecycle learning. BIM is positioned as a structured lifecycle information backbone rather than as a decision-maker. Digital twins, GIS, IoT, enterprise systems, analytics, simulation, and artificial intelligence are treated as enabling capabilities operating within defined governance relationships. The framework further distinguishes requirements validation, requirements verification, and recovery-need outcome assessment; separates physical completion, information completion, and requirement closure; and introduces a proposed governance model for reconstruction requirements that supports provisional satisfaction, closure, reassessment, reopening, and revision. Sustainability and resilience are treated as cross-cutting evidence dimensions informing both prospective intervention decisions and retrospective lifecycle evaluation. The principal candidate contribution is reconstruction justification-to-outcome continuity: the governed preservation and use of traceable relationships between an originating recovery need, the reconstruction and information requirements derived from it, the information and evidence informing engineering assessment and accountable intervention decisions, and the subsequent lifecycle evidence used to verify or reassess reconstruction requirements and evaluate the contribution of resulting interventions to the originating recovery need. The framework is informed by relevant ISO 19650 information-management principles while explicitly distinguishing ISO-supported information-management processes from the reconstruction-specific governance constructs proposed in this research. As a conceptual framework, it requires further expert, case-based, digital, and longitudinal validation. Conceptual Origin. The initial conceptual basis of this working paper emerged from a lecture delivered by the author in Doha, Qatar, in December 2025. The ideas introduced in that academic setting were subsequently developed, expanded, subjected to literature and prior-art review, and formalized into the present research framework.Version: 1.0Publication type: Research Working PaperDOI: 10.5281/zenodo.22884177