This past Sunday marked the end to the successful 14th annual Scientific Computing with Python Conference, more commonly known as SciPy. Roughly 600 attendees from more than 330 organizations throughout the world gathered in Austin, TX, to showcase and discuss their Python-centric mathematics, science, and engineering projects. Among these individuals were several BIDS fellows, staff members, and affiliates.
As the BIDS data scientists gave their talks and discussed their work, it became abundantly clear just how far BIDS and the entire Moore/Sloan Data Science Environment initiative has come in just one year.
At last year’s SciPy 2014, BIDS senior fellow and associate researcher Fernando Perez gave a talk about the then-current atmosphere data scientists encountered in academia, which was (and generally still is) characterized by a relative disregard for the increasing importance of data science in scholarly research and an overly narrow focus on publication count and other traditional evaluation metrics. He introduced BIDS, which was in its infancy, as a place for “people like us,” a place where data scientists in academia can explore, work on, and hopefully overcome some of the issues challenging advances in data-intensive research and career paths.
Fast forward one year to SciPy 2015, and you can see firsthand how this home has started to develop at BIDS. Several BIDS fellows, staff, and members presented their current work/research projects, led tutorials, gave lightning talks, and/or led group discussions, while our ethnography team was on the ground studying the data science landscape.
As the content of these activities reveal, BIDS has created a place for highly skilled researchers from across UC Berkeley and beyond to work together on open source software, reproducible science, education initiatives, and so much more. What’s exciting is that the work presented at SciPy only scratches the surface of what is happening at BIDS; we have numerous other data scientists from outside the Python community who are helping create this home as well as advance the BIDS mission.
We are excited to see where we will be by SciPy 2016 and hope to serve as a model for other universities as they create similar homes for data scientists in academia.
BIDS SciPy 2015 Talks and Tutorials
- Nathaniel Smith and Stéfan van der Walt: “A Better Default Colormap for Matplotlib”
- Stéfan van der Walt: “Image Analysis in Python with SciPy and SciKit Image”
- Katy Huff: “PyRK: A Python Package for Nuclear Reactor Kinetics”
- Mattias Bussonnier: “Jupyter/IPython: State of Multi-User and Real-Time Collaboration”
- Mattias Bussonnier et al.: “Jupyter Advanced Topics Tutorial”
- Jessica Hamrick: “Teaching with IPython: Jupyter Notebooks and JupyterHub”
- Sebastian Benthall: “Exploring Open Source Community Dynamics with BigBang”