Data Studies Program

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The Data Studies program prepares students to navigate and shape an increasingly data-driven world.

Moving beyond computation, this interdisciplinary minor investigates the social, ethical, and relational aspects of data science. Students explore how we gather, organize, and analyze both qualitative and quantitative data to explain and predict global phenomena, learning to apply powerful intellectual methods across a wide range of academic contexts.

An alumni panel discusses the data science career field

Students work with a diverse faculty of experts who bring their discipline’s best practices into the classroom. You will learn to ask the specific questions that data science is uniquely equipped to answer, while critically examining the ethical considerations inherent in the field. This includes learning to identify and address how data-driven work affects costs and benefits for individuals and society as a whole. 

Students develop the critical thinking skills necessary to collect, investigate, and interpret complex information. You will graduate not just with a proficiency in data-driven problem-solving, but with the ability to integrate subject-matter knowledge with technical data to develop new, responsible insights about the world.

The program offers a minor in data studies.

Coursework

Students begin with an introductory statistics course to build a common quantitative literacy. You’ll build on this foundation with courses focused on ethical and moral responsibility, clear and transparent communication, and critically engage with diverse forms of data—quantitative or qualitative, scholarly literature, case studies, or visual media—in the context of geographic, political, environmental, and cultural issues.

Course Requirements

This course provides an introduction to data collection, summarization, and analysis. They will learn how to translate real-world questions they can answer with data science – methods for exploring, visualizing, analyzing, and communicating about data. 

  • MATH 105: Introduction to Statistics

This requirement is met by courses that focus on ethical and moral responsibility or clear and transparent communication. Both goals are critically important for conducting sound data-oriented work.

  • DATA 201: Ethical Issues in Data Science
  • FMST 364: Desiring Machines: AI and Race in Contemporary Media (No Prerequisites)
  • GEOG 340: Geographic Information Systems and Society (No Prerequisites)
  • HIST 112: The History of Technology (No Prerequisites)
  • PHIL 111: Ethics (No Prerequisites)
  • PHIL/ENST 202: Environmental Ethics (No Prerequisites)
  • PHIL 214: Medical Ethics (No Prerequisites)
  • PHIL 211: Ethics and Economics (No Prerequisites)
  • PHIL 335: Contemporary Epistemology (One course in PHIL)
  • WRIT 110: Academic Persuasions: An Introduction to Rhetoric, Research, and the Academic Essay (No Prerequisites)
  • WRIT 203: Argumentation (No Prerequisites)
  • WRIT/FMST 303: The Rhetoric of Data Visualization (No Prerequisites)

This requirement is met by courses that lead students to critically engage with diverse forms of data — quantitative or qualitative, scholarly literature, case studies, or visual media—in the context of geographic, political, environmental, and cultural issues. These courses push students beyond the technical aspects of working with data to focus on the broader context and implications of their data-oriented work.

  • ASIA/GEOG 270: Deep Asia (No Prerequisites)
  • COSC 204: Computing and Society (COSC 102)
  • ECON 219: Chinese Economy (ECON 151)
  • ECON 228: Environmental Economics (ECON 151)
  • ECON 230: The Economics of Poverty in the United States (ECON 151)
  • ECON 231: Inequality and Public Policy (ECON 151)
  • ECON 232: Economics of Education (ECON 151)
  • ECON 233: Economics of Immigration (ECON 151)
  • ECON 234: Gender in the Economy (ECON 151)
  • ECON 238: Economic Development (ECON 151)
  • ENST 200: Environmental Science: Challenges and Solutions (No Prerequisites)
  • ENST 250: Environmental Policy Analysis (No Prerequisites)
  • ENST 233: Global Environmental Health Issues (No Prerequisites)
  • ENST 234: Case Studies in Global Environmental Health (No Prerequisites)
  • ENST 240: Sustainability: Science and Analysis (No Prerequisites)
  • ENST 24: Sustainability and Climate Action Planning (No Prerequisites)
  • ENST 389: Conservation Biology and Policy (No Prerequisites)
  • GEOG 108: Digital Earth (No Prerequisites)
  • GEOG 105: Climate & Society (No Prerequisites)
  • GEOL 311: Environmental Geophysics (No Prerequisites)
  • GEOL 315: Conservation Paleobiology (GEOL 215)
  • GEOL 335: Hydrology and Geomorphology (No Prerequisites)
  • GEOL 370: Geoinformatics (GEOL 190 or higher)
  • GPEH 100: Introduction to Global Public and Environmental Health (No Prerequisites)
  • HIST 306: History of Numbers in America (No Prerequisites)
  • LING 222: The Theories and Practice of Second Language (No Prerequisites)
  • PCON 322: Weapons and War (PCON 111 or PCON 218 or ANTH 218 or SOAN 218 or PCON 225)
  • RELG 254: AI and God: Reconciling Science, Religion, Artificial Intelligence (No Prerequisites)
  • REST 150: Russian Propaganda (No Prerequisites)
  • WRIT 248: Discourses of Race and Racism (No Prerequisites)

Courses fulfilling this requirement expose students to how data-oriented work is done to answer important questions within their chosen discipline. These courses train students to produce knowledge using the best practices of their chosen discipline.

  • ANTH 211: Field Methods and Interpretation in Archaeology (ANTH 102 or ANTH 103 or SOCI 101)
  • ANTH 253: Field Methods and Interpretation in Archaeology (ANTH 103)
  • ASIA 200: Approaches to Asia (No Prerequisites)
  • ASTR 312: Astronomical Techniques (PHYS 232 or ASTR 101 or ASTR 102 or ASTR 210)
  • BIOL/MATH 302: Systems Biology (MATH 161 or MATH 162) and (BIOL 182 or MATH 163 or PHYS 204 or COSC 101)
  • BIOL 316: Bioinformatics (BIOL 181 or BIOL 182)
  • BIOL 320: Biostatistics (BIOL 181 or BIOL 182)
  • BIOL 310: Epidemiology (BIOL 182)
  • CHEM 371: Instrumental Methods (CHEM 263)
  • COSC 306: Algorithmic Game Theory (COSC 202 and COSC 290)
  • COSC 410: Applied Machine Learning (COSC 202 and COSC 290)
  • COSC 426: Natural Language Processing (COSC 202 and COSC 290)
  • ECON 375: Applied Econometrics (ECON 251 and ECON 252 and (MATH 105 or CORE 143S or MATH 316) and (MATH 161 or MATH 162 or MATH 163))
  • EDUC 226: Uses and Abuses of Educational Research (EDUC 101)
  • GEOG 245: Geographic Information Systems (No Prerequisites)
  • GEOG 346: Advanced Geographic Information Systems (GEOG 245)
  • GEOG 331: Environmental Data Science (GEOG 245 or COSC 101)
  • GEOL 215: Paleontology of Marine Life (No Prerequisites)
  • LGBT 220: An Exploration into LGBTQ Studies: Lives, Communities, and Modes of Critical Inquiry (No Prerequisites)
  • LING 200: Science of Language Acquisition  (No Prerequisites)
  • MATH 240: Computational Statistics (MATH 161)
  • MUSE 201: Museum Curating in the Digital Age (MUSE 120 or HIST 120 or ARTH 270 or ANTH 300 or MUSE 300)
  • PHIL 225: Logic I (No Prerequisites)
  • POSC 312: Exploring Politics with Data (No Prerequisites)
  • PSYC 309: Quantitative Methods in Behavioral Research (PSYC 150 OR NEUR 170)
  • RELG 352: Theory and Method in Study of Religion (One course in RELG)
  • SOCI 250: Sociological Research Design and Methods (SOCI 101 or SOAN 101)

Courses fulfilling this requirement are designed to provide students with a more sophisticated understanding of research methods in their discipline or expand their ability to ask and answer nuanced, data-driven questions about the world.

  • One additional course from (3) Human Experience, Public Affairs, and Policy.
  • One additional course from (4) Research Methods from a Student’s Major Program.
  • DATA 400 – Service-Learning Capstone
     

Department Contacts

Chair: Will Cipolli, 315-228-6118
Administrative assistant: Char Howard, 315-228-7719