Data Visualization

Catalog description

This course provides a foundation in the principles, concepts, techniques and tools for visualizing large data sets. DAAN 871 Data Visualization (3) The course provides a foundation in the principles, concepts, techniques and tools for visualizing information in large complex data sets. Unlike scientific visualization, which focuses on the presentation of data that has a spatial or physical correspondence, data visualization focuses on mapping complex, abstract information to a physical representation. The development of effective visualization strategies is crucial for not only facilitating an understanding of large complex data sets but also for driving knowledge discovery and the decision making processes in a given domain. In this course, students will learn the key principles involved in data visualization and will explore a wide range of visualization approaches that can be applied for understanding complex data across different data types. Specifically, techniques for visualizing one-dimensional data (e.g., temporal data); two-dimensional data (e.g., geospatial data); multidimensional data (e.g., mapping relational data in n-dimensional space); hierarchies and graphs (e.g., tree structures); networks (e.g., social networks) and text (e.g., mining text and hypertext from Web) will be discussed. Emphasis will be placed on the identification of patterns, trends and differences in visualizations of data from variety of domains (e.g., science, business, engineering, social media, etc.). In addition, students will gain hands-on experience with a variety of visualization tools including: Gephi, ManyEyes, Excel, Science of Science (Sci2), Pajek, Lattix, R, Cfinder, MapEquation, NodeXL, and/or Gapminder.