There’s a new kind of researcher on campus, one who doesn’t fit into the usual nooks and crannies at a university.
They are data scientists – students, faculty members and professional scientific staff – who are building the tools and crafting the methods to help researchers analyze the vast amounts of data now abundant in every field. The very nature of their skill set is interdisciplinary, and the university system doesn’t always reward them for the time they spend developing techniques and software to advance discovery.
This dilemma, and what universities can do to change it, is the topic of a symposium Feb. 15 at the American Association for the Advancement of Science annual meeting in San Jose, California. The session, “Advancing University Career Paths in Interdisciplinary Data-Intensive Science,” was organized by UW’s Cecilia Aragon and Bill Howe, and also includes UW’s Ed Lazowska, Berkeley’s Joshua Bloom and Fernando Perez, and NYU’s Juliana Freire – partners in the Data Science Environments project supported by the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation.
Read a UW News post here. See Ed Lazowska’s introductory slides here.