In this autumn school, we will build on open-source foundations, focusing on Brightway, Activity Browser, Wurst, and Premise (and maybe Temporalis and ODYM if there is time), to make our inventory models better fit research questions with a temporal dimension. The instructors will be:
- Romain Sacchi: Developer of Premise
- Karin Treyer: Spearheads Brightway’s online learning materials focusing on novice users
- Chris Mutel: Lead developer of Brightway
- Alvaro Hahn-Menacho: Expert in integrating Mass Flow Analysis (using ODYM) in prospective LCA
The course will cover Brightway’s basics and best practices for model development, including the use of Jupyter notebooks and the Activity Browser. Essential LCA aspects such as sensitivity analysis, multiple types of uncertainty, parametrization, and best practices in software architecture will be taught. This includes documentation standards, testing, data and source version control, and linting.
The week starts with three interactive teaching sessions using Jupyter Notebooks, Git, and other tools needed to properly develop, test, and document LCA models. These notebooks include exercises, and solutions will be discussed in class. From Thursday to Friday, you will work in groups of around five people on small group projects, applying these ideas. Short teaching inputs will support the group work. Groups will present their results on Friday afternoon.
This autumn school is aimed at students who wish to become familiar with the Brightway ecosystem, specifically targeting beginner and intermediate users. Students who complete the school will receive a certificate for 2 ETCS credit points. Enrollment is limited to 30 people.
The summer school will be held at the Möschberg seminar hotel, in Grosshöchstetten, Switzerland. This hotel is located outside the village, offering views south towards the Bernese Alps. Möschberg emphasizes local and organic food for its guests.
A basic understanding of Python is necessary for the school. Brightway offers training and documentation online. Students should review those materials and some Python training before the school starts. Also, read the INSTRUCTIONS.MD file in this repository.
- Starting Time: The school starts at 09:00 on Monday. It is most convenient to arrive on the 8:04 train into Grosshöchstetten (or the day before).
- Ending Time: The school ends at 17:00 on Friday. An Apéro with snacks and drinks will
- be offered on Friday evening. You can contact the hotel if you wish to stay
- Friday night or arrive before Monday morning.
For more information, please see the schedule.
Ideally, do this at least one week before the course starts, so that you have time to ask/write us questions if you encounter any issues. Please read the INSTRUCTIONS.MD file in this repository.
During the group projects, you will be asked to work on a topics. You may choose a topic of your own and form a group around it. Or you may choose one of the topics described in TOPICS.MD. Please acquaint yourself with the topics before the school starts.
Unless otherwise specified, all material in this repository is licensed under the BSD 3-clause license. See the LICENSE.md file for more information.
For any questions or further information, please contact the organizing team.
Please refer to the INSTRUCTIONS.MD file in this repository.