Project Jupyter is a community of open-source developers, scientists, educators, and data scientists. Its goal is to build open-source tools and create community that facilitates scientific research, reproducible and open workflows, education, computational narratives, and data analytics. Jupyter supports over 100 programming languages, and connects data analytics tools across a range of disciplines and communities.
There are several core projects of Jupyter that the Berkeley Institute for Data Science supports:
rOpenSci is a software collective that provides R-based tools to enable access to scientific data repositories, full text of articles, and science metrics and also facilitate a culture shift in the scientific community toward reproducible research practices.
Software Carpentry is a volunteer organization whose goal is to make scientists more productive and their work more reliable by teaching them basic computing skills.
Opportunities for Biological Discovery From Quantitative Analysis of Vast Data Sets Acquired with Advanced Microscope Technologies
As more scientific fields move to intersect with computation, a need arises for software tools that can bridge the gap between the matter under investigation and computational principles/software engineering. Many scientists are specialists trained in their respective domains, so finding contributors with the necessary practical experience to implement computational tools—be it for statistical analysis, data wrangling, machine learning, visualization, or data management—can be difficult.