Data Science Hub Updates: December 2017

The June 2017 public meeting about a campus-wide Data Science Hub led to the formation of a 9-person Steering Committee co-led by Michael Ferris, Brian Yandell, and Eric Wilcots. The other members of the Steering Committee are Katherine Curtis, AnHai Doan, Kristin Eschenfelder, Lauren Michael, Rob Nowak and Paul Rathouz (see bios on web page). In the past 6 months, we have focused on developing key aims and writing a proposal for seed funding.

In the last decade, data science has gone from a “big data” fad to a mission-critical enterprise need. With modest investment, UW-Madison could become an international leader in data science. The goal of DSHub is to leverage existing campus data science expertise to coordinate and execute data science strategy via a much needed campus-wide research network that fills critical gaps and supports data science growth and cross-fertilization. Over the coming 4 years, DSHub proposes the following three specific aims:

Aim 1: Create a central data science concierge office (web portal, physical location, and senior consulting personnel) as the first stop for campus and industry partners with data science needs.

Aim 2: Create a data science training nucleus to attract new audiences for data science training; coordinate development of modular data learning material; and increase visibility and cross-fertilization of data science courses and workshops.

Aim 3: Create a collaborative data science ecosystem to identify data bottlenecks in key research projects and quickly build support teams to overcome challenges.

DSHub is submitting a UW2020 proposal in December to realize Aim 1 and begin to meet Aim 2. We encourage collaborators to submit Data Science Initiative (DSI) proposals in March to address Aims 2 and 3. Additional Aim 2 training nucleus funding will further expand the community of data science trainers through new workshops and bootcamps and increased connections (including resource and personnel sharing) among other data science collaborative units. To meet Aim 3, we encourage teams across campus to build capacity for data science within their domain by submitting DSI proposals that include data science training of selected staff to build sustainable expertise within their team. We will connect these domain staff with our training nucleus to identify bottlenecks in key research projects and to quickly build support teams to overcome those challenges.