Successful adoption of data science will require several linked efforts. Domain scientists need training in the foundations of data science, including programming, statistics, and reproducible computational science, while methodological scientists need training to work productively in domain areas. This working group addresses these needs through a combination of activities, including workshops and bootcamps.
The current system for career advancement in research universities, which is heavily weighted toward publication, often does not align with what makes a modern data scientist successful. This working group aims at identifying and promoting alternative metrics and career paths that lead to growth and advancement opportunities for scientists who do not fit the typical academic mold but are critical to its success.
The Berkeley Ecoinformatics Engine provides access to biodiversity information from the university’s rich and diverse repositories as well as tools to promote visualization and in-depth analysis.
