Abstract:

A Jupyter notebook, a preprint from arXiv, and a Stack Overflow code snippet. What do they all have in common?

All convey complex ideas from a writer to an audience. However, the tools to create and read them have not kept pace with the complexity of their contents. What would it look like if we had tools as sophisticated as state-of-the-art IDEs (integrated development environments, like Visual Studio or IntelliJ) for authoring and reading these artifacts? What interactions would they provide? What algorithms and models would they need?

In this talk, I discuss novel core requirements for reading and writing complex information artifacts, and reify these in the design and implementation of IDEs for Ideas. One IDE lets you click on results in a messy Jupyter notebook and trace the code that computed it. Another brings the meaning of scientific papers to life. Come to this talk to learn about the challenges we face using complex information artifacts every day, a vision of how our tools should help, systems embodying this vision with novel interactions and algorithms, and evidence from usability studies validating their design.