Community-level data science and its spheres of influence: beyond novelty squared

Brittany Fiore-Gartland and Anissa Tanweer Data science has many characterizations, but in academia it is often talked about as pushing the limits of both methodological and domain science, what Josh Bloom, a Professor of Astronomy at U.C. Berkeley, has referred to as “novelty squared”. Bloom sees this as the “great challenge of modern interdisciplinary scientific collaboration”. The idealized characterization of data science in academia is also represented in the idea of shifting from the traditional T-shaped scientists, who have deep expertise in a single domain, to Π (Pi)-shaped  scientists with deep expertise in both a domain and methodological science (as coined by Alex Szalay and discussed here and here. As Π-shaped data scientists, they are primed to innovate in multiple disciplinary trajectories. Bloom and others have argued that these characterizations…


Link to Full Article: Community-level data science and its spheres of influence: beyond novelty squared