Data Science in the Liberal Arts
By Lina Sorg
The prevalence of big data continues to grow in today’s world. Analysis of this data plays a vital role in scientific research, but also finds widespread application in marking and product development, public health, and climate science, among other fields. As a consequence of expedited data collection, universities are beginning to implement programs that further expose students to data science and analytics. Because the collection of large quantities of data is becoming routine, data analysts will have to do more than just gather and manage data. They will need to communicate well, ask relevant questions, and address ethical concerns to reveal historical patterns and modern-day practices that ultimately lead to a better understanding of the natural world. Thus, the well-rounded liberal arts sector might just be an ideal area for university recruitment.
In the fall of 2015, Macalester College’s Department of Mathematics, Statistics, and Computer Science introduced a minor in data science, designed specifically for students outside the majors of applied mathematics and statistics. Karen Saxe, the DeWitt Walace Professor at Macalester, discussed the program during a minisymposium talk entitled “Data Science: A Natural Fit in the Liberal Arts Curriculum” at the SIAM Annual Meeting. “Data science is very much a liberal arts subject.” Saxe said. “It aligns well with the college’s strategic plan.” Macalester College is a liberal arts college with a student body of around 2,000.
Creation of a data science minor was driven by student interest and took two years to implement, Saxe said. She added that many students were already taking some of the required courses, such as “Introduction to Statistical Modeling” or “Core Concepts in Computer Science.” A growing number of students are also attending graduate school for or beginning careers in data science. Students pursuing the minor must take two computer science and two statistic courses, all from a pre-approved list, as well as two courses in a domain area in which data science is used. Possible domains include but are not limited to ecology, environmental science and policy, data-driven journalism, political analytics, and quantitative economics. “There are no explicit requirements for math,” Saxe said, “but a lot of statistics courses have calculus or linear algebra as prerequisites.”
After the required coursework, students must also write an integrative essay discussing a completed data science project or proposing a project in their chosen domain area. “A lot of our students are very motivated by problems of humanity,” Saxe said, adding that successful past projects reported on police brutality and the farm-to-table food movement. Additionally, a ‘Doctors without Borders’-style club for data science is beginning to form on campus.
Trained data scientists can find employment at government agencies, science institutes, and retail companies that analyze large amounts of data to drive their business, such as Amazon, Target, or Netflix. Saxe went on to list additional fields of employment, including healthcare, journalism, biotech, finance, insurance, hospitality, manufacturing, and transportation. In our rapidly-changing world, future data scientists will need to unite interdisciplinary teams in interdisciplinary fields, and effectively communicate their findings to both the public and decision-makers. Exposure to the liberal arts will only facilitate this process.
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Lina Sorg is the associate editor of SIAM News. |