| Summary: | Environmental metrics play a significant role in behavioural change, policy formation, education, and industrial decision-making. Life Cycle Assessment (LCA) is a powerful framework for providing information on environmental impacts, but LCA data is under-utilized, difficult to access, and difficult to understand. Some of the issues that are required to be resolved to increase relevancy and use of LCA are accessibility, validation, reporting and publication, and transparency.
This thesis proposes that many of these issues can be resolved through the application of open frameworks for LCA software and data. The open source software (OSS), open data, open access, and semantic web movements advocate the transparent development of software and data, inviting all interested parties to contribute.
A survey was presented to the LCA community to gauge the community’s interest and receptivity to working within open frameworks, as well as their existing concerns with LCA data. Responses indicated dissatisfaction with existing tools and some interest in open frameworks, though interest in contributing was weak. The responses also pointed out transparency, the expansion of LCA information, and feedback to be desirable areas for improvement.
Software for providing online LCA databases was developed according to open source, open data, and linked data principles and practices. The produced software incorporates features that attempt to resolve issues identified in previous literature in addition to needs defined from the survey responses. The developed software offers improvements over other databases in areas of transparency, data structure flexibility, and ability to facilitate user feedback.
The software was implemented as a proof of concept, as a test-bed for attracting data contributions from LCA practitioners, and as a tool for interested users. The implementation allows users to add LCA data, to search through LCA data, and to use data from the software in separate independent tools..
The research contributes to the LCA field by addressing barriers to improving LCA data and access, and providing a platform on which LCA database tools and data can develop efficiently, collectively, and iteratively.
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