Brightcon 2025, hackathon & courses in Grenoble and online

Despite the increasing importance of FAIR data (Findable, Accessible, Interoperable, and Re-usable) in academic research, structured data management remains an often-overlooked challenge in the life cycle assessment (LCA)-community. Most researchers work independently on separate projects and tools, which leads to isolated LCA models, little exchange of reusable data and repeated modelling of similar processes with inhomogeneous data quality.

To address this issue, we are developing a shared library of Life Cycle Inventories for energy and process systems based on Brightway. The goal is to collect and organize existing models from different projects, publications and literature in a central cloud database that is intuitive, well-documented and accessible to all members of the research group. The workflow for building and using the database consists of the following steps:
(1) Structured data submission: Researchers submit process data into a structured Excel template.
(2) Automated data integration: Submitted data is automatically processed and imported into a cloud-based Brightway database.
(3) Metadata and documentation: Each entry is stored together with metadata and full documentation.
(4) Search and export functionality: Users can search the database for specific processes and export them either as Brightway activities or in Excel format, ready to be used in new projects.

Furthermore, our approach raises important discussion points in LCA collaboration such as how to reduce redundancy, ensure data quality in modelling, and how to enable more efficient collaboration. Special attention is given to academic needs: proper authorship attribution, data confidentiality for varying project types (research, teaching, industry), and accessibility for users without prior Brightway experience. Further features, which could be integrated in the future, include version control, variable parametrization, and the integration of automated standard analysis tools (e.g. contribution or uncertainty analysis). The setup of the database should also consider possible interfaces to external modelling software (e.g. chemical process models).

We propose this contribution to share our approach, discuss practical challenges in academic data collaboration, and explore how the Brightway community can support research workflows beyond individual projects.