A module dataset is a structured set of Exchanges with fixed mathematical relationships and accompanying documentation, designed to function as reusable plug-ins within Life Cycle Assessment databases and impact assessment frameworks.
The defining characteristic of a module dataset is the presence of fixed mathematical relationships between the exchanges it contains. These predetermined relationships ensure consistency and reproducibility when the module is applied across different contexts. The module effectively encapsulates a specific calculation routine or data structure that can be repeatedly deployed without requiring reconfiguration of its internal mathematical logic.
Module datasets serve dual purposes within LCA modelling. Firstly, they can be integrated into Activity datasets during the linking phase, where they provide standardised exchange data that connects activities within a product system. Secondly, they can be incorporated into Impact category datasets to support Impact assessment calculations, providing the mathematical foundations for converting inventory data into impact indicators.
The plug-in nature of module datasets reflects their modular architecture. Rather than embedding the same mathematical relationships and exchange data repeatedly across multiple datasets, practitioners can reference a single module dataset wherever needed. This approach improves database maintainability, reduces redundancy, and ensures that updates to a module automatically propagate to all datasets that employ it.
Documentation forms an integral component of each module dataset, providing transparency about the mathematical relationships, data sources, assumptions, and appropriate applications. This documentation enables users to understand when and how to apply specific modules correctly within their LCA models.
