Anil Madhavapeddy, Professor of Planetary Computing

Scientists increasingly write software as part of large-scale collaborative workflows, but current tools make it difficult to follow FAIR principles (findability, accessibility, interoperability, reusability) and ensure reproducibility by default.

This paper proposes Fairground, a computational commons designed as a collaborative notebook system where thousands of scientific artifacts are authored, collected, and maintained together in executable form in a manner that is FAIR, reproducible, and live by default.

Unlike existing platforms, Fairground notebooks can reference each other as libraries, forming a single planetary-scale live program executed by a distributed scheduler. We describe the design of Fair Python, a purely functional subset of Python, and a foreign function interface for interoperating with existing code. Through three interleaved research tracks focusing on language design, interoperability, and distributed execution, we aim to create a next-generation collaborative scientific workflow system that makes best practices the path of least resistance.