UC Berkeley statistics Professor Bin Yu describes Data Science as a “field of evidence-seeking that combines data with information from a research domain information to generate new knowledge.” Concerned with making this process more consistent and trustworthy, Bin has laid out her framework for integrating predictability, computability and stability (PCS) in a paper called “Veridical data science” (veridical meaning “truthful” or “coinciding with reality”), co-authored with her former student Karl Kumbier (now a postdoc at UCSF) and published in the Proceedings of the National Academy of Sciences in February 2020: https://www.pnas.org/content/117/8/3920.

Read more about Bin’s research at https://data.berkeley.edu/people/bin-yu.