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Aaron Culich's picture

Jetstream cloud support for multi-institutional data science workshops and research

Jupyter notebook showing neuroimaging visualization, over Jetstream banner

Data scientists at the Berkeley Institute for Data Science (BIDS) and the University of Washington’s eScience Institute teamed up with UCSF researchers to deliver a workshop on data-driven analysis and machine learning for neuroscience imaging data. The workshop was held in January 2017, and had 30-40 participants comprised of faculty, postdocs, graduate students, and data science fellows from UCSF, UC Berkeley, Lawrence Berkeley Lab, and the University of Washington.

Welcome to Research IT's Spring 2017 Interns

Research IT welcomes two UX/Visualization Interns, a Container Research and Development Intern, and a User-Centered Design Research Intern to our team for the Spring 2017 semester! Samba Njie Jr., one of our UX/Visualization Interns, will be generating visualizations and reports for Berkeley Research Computing metrics. Cassie Zhang, our other UX/Visualization Intern, will be prototyping a “dashboard” for the Savio High Performance Compute cluster, to show researchers how they are using their Faculty Compute Allowance.

CollectionSpace Reporting

https://webapps.cspace.berkeley.edu

Reporting on collection data managed with CollectionSpace is complicated by the variation of data models and collection types used by diverse museums and collections that employ the software. Flexible modes of generating reports -- from use of the built-in JasperReports reporting tool or extension points in the codebase, to development of web applications that address the CollectionSpace API or database -- allow users to address this complexity in ways that best suit their collection and institutional workflow. 

Survey launched about “Understanding researcher needs and values about software”

Software is as important as data when it comes to building upon existing scholarship. However, while there has been a small amount of research into how researchers find, adopt, and credit software, there is currently a lack of empirical data on how researchers use, share, and value software and computer code.