Why
Why make lemonade out of lemons?¶
The idea for this project started behind the concept of failure (
lemons) in data science collaboration, and how to successfully address these failures to make lemonade.
Technical and non-technical barriers to effective collaboration often hamper progress, especially when highly productive groups with diverse expertise and computational backgrounds work on common problems.
Overcoming these barriers and learning from collective experience is critical for ensuring successful outcomes.
The two-part workshop series will be conducted in an idea/innovation labs format with meeting facilitators.
The goal is to bring together thought-leaders and practitioners in data-driven open science projects with participants from areas emphasizing Astronomy, Earth Sciences, Computational and Information Sciences, Mathematics, and Cyberinfrastructure.
We’ve dubbed the two workshops “Lemon” and “Lemonade” labs.
During the Lemon Lab (Spring 2019), we openly discussed challenges in inter- and transdisciplinary collaborations and brainstorm ideas on improve productivity and outcomes. Our publication "Ten simple rules to cultivate transdisciplinary collaboration in data science" was grown out of that effort.
At the subsequent Lemonade Lab (Fall 2022), participants will prototype ideas and solutions identified during the Lemon Lab workshop in a codefest/hackathon-style event — turning “lemons” into thirst-quenching “lemonade.”
How could you create the ML knowledge commons for your science domain?