Issue 3.2, Spring 2021

From the Editor-in-Chief

Building Data Science Infrastructures and Infrastructural Data Science

by Xiao-Li Meng

Issue 3.2 / Spring 2021

Panorama

Overviews, Visions, and Debates

A Conversation With Michael V. Drake and Jennifer Chayes

by Michael V. Drake, Jennifer Chayes, and Xiao-Li Meng

An interview with Michael V. Drake and Jennifer Chayes by Xiao-Li Meng

Featured Discussion

Data Science and Computing at UC Berkeley

by Jennifer Chayes

by Munther A. Dahleh

Data Science in Domains: Interaction of Physical, Social, and Institutional Systems

by David Madigan

Supra-Disciplinary Data Science

by S. Joe Qin

Data Science Education With Domain Knowledge and System Principles

by Hal S. Stern, Debra J. Richardson, and Marios Papaefthymiou

Data Science and Computing: The View From a Sister Campus

by Patrick J. Wolfe

Leadership in Data Science: Lessons Learned From Time Invested in Helping to Build the Field

Urban Sustainability Observatories: Leveraging Urban Experimentation for Sustainability Science and Policy

by Harvey Miller, Kelly Clifton, Gulsah Akar, Kristin Tufte, Sathya Gopalakrishnan, John MacArthur, Elena Irwin, Rajiv Ramnath, and 1 more

Enhancing and Accelerating Social Science via Automation: Challenges and Opportunities

by Tal Yarkoni, Dean Eckles, James A. J. Heathers, Margaret C. Levenstein, Paul E. Smaldino, and Julia Lane

Connections

Supplements (2):

Beth Simone Noveck

•

Julia Lane

Cornucopia

Impact, Innovation, and Knowledge Transfer

Modern Machine Learning and Particle Physics

by Matthew D. Schwartz

Stepping Stones

Learning, Teaching, and Communication

Featured Discussion

Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley

by Ani Adhikari, John DeNero, and Michael I. Jordan

by Allen B. Downey

A Decision Tree for Introductory Data Science

by Aleksandrina Goeva, Peyton Jones, Sara Stoudt, and Ana Trisovic

Recipes for Connector Courses From the Early-Career Board Kitchen

by Alan David Fekete

Variations in Data Science Curriculum: A View From Computing Education

by Alison L. Gibbs and Nathan Taback

The Building Blocks of Statistical Education in the Data Science Ecosystem

by Yolanda Gil

More Computing and Less Programming: A Proposal to Broaden Participation in Data Science

by Brian Kim

Scaling Up Data Science for the Social Sciences

by Michael J. Franklin and Dan L. Nicolae

A Perspective on Designing Undergraduate Education in the New Discipline of Data Science

by Alfred Z. Spector

Data Science Goals and Pragmatics

by Dustin Tingley

Building on the Shoulders of Bears: Next Steps in Data Science Education

by Chris J. Wild, Tom Elliott, and Andrew Sporle

On Democratizing Data Science: Some iNZights Into Empowering the Many

Something New Is Afoot in Academia

by Ani Adhikari, John DeNero, and Michael I. Jordan

Milestones and Millstones

Foundations, Theories, and Methods

A Geometry-Driven Longitudinal Topic Model

by Yu Wang, Conrad Hougen, Brandon Oselio, Walter Dempsey, and Alfred Hero

Minding the Future

Building Pipelines for Data Science

Column Editor: Nicole Lazar

Engaging Young Learners With Data: Highlights From GAISE II, Level A

by Leticia Perez, Denise A. Spangler, and Christine Franklin

Mining the Past

Brief Histories of Data Science

Column Co-Editors: Stephanie Dick and Christopher J. Phillips

Lessons From the ‘Data Exhaust’ of Plantation Slavery

by Caitlin Rosenthal

Recreations in Randomness

Data Science for Leisure Activities

Column Editor: Mark Glickman

Computers Learning Humor Is No Joke

by Thomas Winters

Bits and Bites

Comment on "Reproducibility and Replication of Experimental Particle Physics Results"

by Andrew Fowlie

A Letter to the Editor