Highlights / Discussion Points

• Introducing MODASTI, a proposed open-source platform for modular and composable LCIA configurations
• Exploring whether there is a community need for transparent, interoperable, and collaboratively maintained LCIA infrastructure
• Discussing modular schema design, provenance, versioning, and persistent identifiers for reproducible LCIA compositions
• Examining technical, institutional, and social barriers to collaborative LCIA development and adoption
• Collaborative prototype discussion and hands-on exploration of implementation concepts using Python- and Brightway-compatible structures

Concise Description

Modern life cycle impact assessment (LCIA) frameworks are typically assembled from methods, datasets, and modeling approaches developed across multiple research groups and domains. However, many existing frameworks remain difficult to inspect, adapt, or incrementally improve at the level of individual methodological components. Smaller contributions such as updated fate factors, revised regionalization approaches, mappings, normalization references, or background datasets are often embedded within larger institutional frameworks and can become difficult to trace, reuse, or openly maintain. At the same time, practitioners and method developers increasingly work in contexts where selective adaptation of existing LCIA approaches may be scientifically useful or regionally necessary.

This workshop introduces MODASTI, a proposed open-source platform concept for constructing, modifying, and sharing composable LCIA configurations from interoperable modules with explicit provenance and persistent identifiers. The concept spans multiple levels of modularity, ranging from combining existing midpoint indicators across frameworks to modifying submodules such as fate or effect models, and ultimately adapting underlying spatial aggregations or background data. Rather than proposing another integrated LCIA framework, MODASTI aims to explore whether a community-driven infrastructure for transparent and reproducible LCIA composition would be valuable and feasible.

The session will combine a short conceptual introduction and prototype demonstration with collaborative discussion and hands-on exploration of implementation concepts. Topics will include modular schema design, metadata requirements, interoperability, governance, and barriers to adoption. The prototype will be based on open-source Python tooling with an emphasis on interoperability with Brightway and exportable data structures.

By emphasizing transparent compositions, reproducible identifiers, open contribution pathways, and collaborative infrastructure development, the workshop aims to foster discussion around more accessible and community-maintained LCIA ecosystems.