Data Science is the study of data and the methods used to transform data into knowledge. Data scientists study how different data structures capture and encode information; how and when data should be interpreted as scientific evidence; how data enables prediction machines and informs forecasting; how data-derived knowledge impacts science, society, and policy; and how ethical standards govern the use of data. Data scientists also develop mathematical and computational frameworks to extract knowledge from data and generalize findings.

Data Science is often envisioned as the application of statistical and computational tools to real-world problems, but the discipline is broader than just its applications. Data scientists contribute to the mathematical theory of statistics and computer science; they develop and study the behavior of computational algorithms; they examine how the collection of data impacts its utility and validity; how data should be stored, shared, and communicated; how and why machine learning works; and how modern computational advances have created new ethical dilemmas for societies, companies, and governments.

Here at the University of Virginia’s School of Data Science, we think of data science as consisting of:

Domain Examples
Analytics prediction modeling, machine learning, algorithm development, statistical methods, imaging, computer vision
Data Engineering data pipelines, machine learning ops, data life cycle
Data Structures data architecture, database theory
Data Systems high performance computing, distributed systems, cloud architectures, security
Data Coalescence communication, visualization, human-computer interaction
Data Policy & Ethics privacy, ethical algorithmic construction and deployment, representativeness
Social Impact justice and influence pertaining to the use of data and analytics
Utilization practical applications of data science techniques at scale


We have combined these topics into Domains of Data Science, which we use as a self-organizing principle for our School. Our data scientists use statistical, computational, and philosophical principles to enhance ongoing collaborations in environmental science, life sciences, biomedical science, engineering, humanities, education, and business.  

Exploration. Scholarship. Impact. @ UVA Data Science