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.
The Berkeley Demography Lab is the cloud computing facility for the Berkeley demography community. The lab provides a computing environment optimized for research and teaching in demography. All of the popular tools of data science and statistics are supported, and consulting help is available from our professional staff and wider community. Users have access to large amounts of disk space and sufficient RAM to operate on large social science datasets either remotely or using workstations in our computer lab.