Structured publication of life cycle assessment models and results
Many of the challenges facing interpretation and knowledge synthesis from life cycle assessment (LCA) studies stem from the inability of study authors and readers to formally agree on the structure and content of life cycle inventory models. This article presents a framework for LCA study authors to publish inventory models in a structured format based on a mathematical formulation of a foreground study. Using linked semantic data as a foundation, the publication framework offers a mechanism to provide both machine readability and unambiguous human interpretation of published studies. Implementing the framework requires only that the LCA community provides a way for study authors to make common reference to shared data sources, including background databases, elementary flows, and impact assessment methods, that are widely used in many studies. The framework contributes to ongoing efforts within industrial ecology to improve the reproducibility and verifiability of scholarly works, and lays a course toward distributed, platform-independent computation and validation of LCA results.