Bachelor of Science in Social Data Science
- Katherine Worboys Izsak
The new undergraduate major (BS) in Social Data Science (SDS) combines courses from multiple disciplines to prepare students to effectively, ethically and efficiently create high quality information products (such as datasets, visualizations, and models) that represent human activity and behavior. Data science is increasingly critical to decision-making in numerous fields. Just as important is understanding the ethical, legal, and social responsibilities of representing and interpreting data about people. Social data science encompasses all elements of the data life cycle, including measure conceptualization, data gathering, management, manipulation, analysis, presentation, archiving, and re-use. Further, effective and appropriate construction, analysis, and use of social data requires understanding social science theory and domain expertise. The program’s core courses will prepare students to work with data science practices, technologies, tools, and sources across disciplines and industries, while the track courses will provide students with opportunities to apply these skills while gaining expertise in a particular social science context.
What do our students learn in the program?
Design, execute, document, and disseminate research that applies tools and methods from data science to address a social science research question;
Develop expertise in specific contemporary social science theories and data science approaches to tackling research questions related to these theories;
Apply findings from social data science research to analyze the policy and design of socio-technical systems; and
Identify and analyze social, legal, and ethical and equity issues in social data science work and in the profession.
What courses do our students take?
SDS students take a set of core courses housed in the iSchool and BSOS’s Joint Program in Survey Methodology (JPSM). They then select a track discipline in the College of Behavorial and Social Sciences or the School of Public Health, in which they train in relevant theory and methods, from among the following options:
African American Studies
Anthropology
Economics
Government and Politics/International Relations
Geography/Geospatial Information Science
Psychology
Public Health Sciences
Sociology
The program requires 51-59 credits. The core courses include foundational courses in programming, statistics, mathematics, and data science, as well as upper-level courses in database design, data privacy and security, ethics, data sources and manipulation, data visualization, survey fundamentals, and questionnaire design. Students also take a set of track courses in a discipline that include introductory benchmark courses, upper-level method and theory courses, and a set of restricted electives that will allow students to deepen their knowledge of the discipline and apply data science principles to social science research and practice. Students finish the program by taking a required capstone course.
Who are our students?
SDS students are a wide and diverse array of people with an interest in working with social data in order to advocate for their perspectives, needs, and communities. Students should have an interest in learning programming, statistics, and social theory, and an interest in applying those skills to social science challenges.
Where do our students go?
The 2016 UMD Strategic Plan identifies data analytics, especially the process of creating and analyzing large data sets or big data, as an area of “almost desperate national need.” SDS students will address that need in data science jobs across a variety of industries, including government, healthcare, sustainability, economics, entertainment, human rights, equity and diversity, and many others.