Environmental product data ecosystems remain structurally fragmented, limiting the reliable integration of lifecycle environmental information within digital building workflows. Although Environmental Product Declarations, Building Information Modeling-based Life Cycle Assessment, and Digital Product Passport frameworks are increasingly adopted, their effective interoperability is constrained by data-level deficiencies that existing research has not systematically characterized. This study addresses that gap through a proposal-oriented systematic review of 57 peer-reviewed studies conducted according to the PRISMA frameworks, with the objective of identifying foundational data-level requirements for machine-readable and interoperable environmental data exchange in digital building environments. Six recurring data-quality gap categories are identified, each reported in 21.1-26.3% of the reviewed studies: poor data quality and uncertainty, absence of unique identifiers and traceability mechanisms, dependence on manual mapping, lack of machine-readable data structures, harmonization deficiencies across standards and program operators, and inconsistent definitions of core lifecycle parameters. The relatively similar reporting frequencies across categories, together with recurring co-occurrence patterns, indicate that the reviewed literature addresses multiple interrelated dimensions of environmental data fragmentation rather than a single dominant limitation. From these findings, three associated foundational conditions are extracted and formalized as a conceptual basis for future digital environmental data systems: structured and harmonized environmental data foundations, semantically interoperable and traceable data exchange structures, and governance-aligned lifecycle data coordination frameworks. The review further positions DPPs as an emerging product-level data layer that could support structured product information, traceability, and information reuse within BIM-LCA workflows, while not constituting an established end-to-end implementation framework.
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POURHOSSEINI et al. (2026) studied this question.
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