Brightcon 2026, hackathon and courses

Context
At Brightcon 2025, Départ de Sentier highlighted three fundamental life cycle assessment (LCA) data-related challenges (findability, maintenance, and flexibility) and decided to focus on three solutions: vocabulary, models, and data [1]. Although the community recognizes the need for FAIR (findable, accessible, interoperable and reusable) principles in LCA data, the landscape remains fragmented regarding these principles [2,3]. To the best of our knowledge there exists no systematic review of LCA data formats (i.e., schemas and serialization formats). This gap creates a dual risk: it leaves LCA practitioners without a roadmap to navigate software and data format silos, and it prevents developers from leveraging historical design choices to inform he development of future data formats. Furthermore, most of the studies discussing LCA data formats seem Western-centric, potentially overlooking significant data format developments from East Asia and the Global South.
Approach
This study provides the first systematic review of LCA data formats. We include 100+ studies in the review to summarize the benefits, limitations, and silos of current data formats. The raw data and resulting visual representations will be available on GitHub. This allows the review to be updated dynamically, transitioning from a static study to a functional resource for the community.
The Brightcon Spirit
We aim to make this work collaborative. Through open-source collaborative public repository, we invite the LCA community to expand the review beyond Western-centric sources. This ensures that the findings remain relevant as new LCA methodologies, databases and software emerge globally, directly supporting the goal of identifying and overcoming data silos in sustainability practices.

[1] Mutel C. (2025). Keynote: Départ de Sentier and friends: The next 12 months. Available at https://youtu.be/RyxDtk_J1OU?si=8wwxq5BvFDYjgYW_ (Accessed 23/04/2026)
[2] Ghose, A. (2024). Can LCA be FAIR? Assessing the status quo and opportunities for FAIR data sharing. The International Journal of Life Cycle Assessment, 29(4), 733-744.
[3] Xu, C., Jia, T., Qi, J., Cai, Z., Zhang, R., Xiong, R., ... & Xu, M. (2025). Addressing critical challenges towards a robust data system for life cycle assessment. Nature Reviews Clean Technology, 1(11), 788-800.