A new data science initiative from Brown University will give students innovative educational opportunities around big data use.
The data science initiative also will catalyze new research programs to address some of the world’s most complex challenges.
The initiative builds on established strengths in mathematical and computational sciences and a long history of data-related research across its core academic departments.
“The Data Science Initiative will … unearth new methods for using big data to solve big problems,” said Brown President Christina Paxson.
Despite recent advances, growth in the volume and complexity of data continues to outpace the development of new techniques needed to translate these data into cutting edge research. At the same time, the application of big data to new questions and disciplines requires novel approaches.
In its initial stages, the data science initiative will include a new one-year master’s degree in data science, expanded undergraduate course offerings, and the addition of 10 new faculty members and researchers whose research and teaching will focus on fundamental methods of data science and their application to a variety of research questions.
(Next page: The data science initiative’s alignment with educational goals)
The Data Science Initiative aligns with Brown’s commitment to taking an integrative approach to developing solutions to complex challenges — an approach that bridges and unites multiple academic areas of research and study. Brown’s departments of mathematics, applied mathematics, computer science and biostatistics will serve as the initiative’s hub, but a key focus will be to create a campus-wide community in data science, engaging students and faculty in life and physical sciences, social sciences and the humanities.
Ultimately, the initiative aims to ensure that scholars across Brown’s disciplines become fluent with data in a way that encourages them to integrate data science into their teaching and research in novel and creative ways.
“Different types of data — genome sequences, data from social networks and medical records, to name just a few — are giving rise to entirely new frameworks and theories on how to extract meaning from data,” said Jeffrey Brock, chair of the Mathematics Department and director of the initiative. “We want to explore fundamentally new techniques and methods for eliciting new knowledge from data.”
In addition to more traditional research projects in the life, physical and social sciences, scholars from the data science initiative will work with Brown’s Cogut Center for the Humanities to seek new connections across the cultural divide between the sciences and humanities and ways of using data in new scholarly contexts.
Partnerships with Brown’s Watson Institute for International and Public Affairs and the Center for the Study of Race and Ethnicity in America will investigate the societal and cultural impacts of data, including questions related to data access, privacy, security, equity and justice.
“As the use of big data expands in commerce, public policy and in our everyday lives, it presents new challenges that cut across disciplinary boundaries,” said Brown Provost Richard M. Locke. “Brown’s Open Curriculum and collaborative research ethos put us in a unique position to help chart the future of the data-enabled society.”
The management consulting firm McKinsey & Company estimates that by 2018, the U.S. will have a shortage of 1.5 million managers capable of using data analysis to make informed decisions. There will be an additional shortage of as many as 190,000 employees with deep data skills necessary to develop complex analyses and communicate findings through visual media.
To prepare students for the data-enabled economy, faculty in the data science initiative will partner with departments across campus to create data science course sequences to promote data fluency in students studying in a variety of disciplines. New faculty added through the initiative will expand the course options already available at Brown. Current course offerings include two introductory courses — “Data Fluency for All” in Computer Science and “What’s the Big Deal with Data Science” in Applied Math — both designed to introduce the field to students without much experience with data science techniques.
The master’s program, which began recruiting its initial cohort this month, will offer a deeper dive into the methods applied by data scientists. In addition to a core curriculum focusing on foundational mathematical and computational techniques, an elective class will let students explore particular applications of their choice. A capstone project will help students apply what they’ve learned to real-world questions and problems.
“The program aims to provide students with the deep data fluency necessary for leadership in data-centric careers,” said Carsten Binnig, adjunct professor of computer science and director of the master’s program. “Courses will provide a fundamental understanding of the tools of data science that students can apply in a huge variety of careers, whether in business, health care delivery, academic research or something else.”