Today’s world is driven by data. Political, economical, and environmental decision making is increasingly based on larger data sets, and advertisers and services like Google personalize what you see and are offered based on data about you and “customers like you.” Moreover, social media allow the public to directly participate in decision making, disaster reporting, and humanitarian interventions. In order to do this, massive amounts of data need to be collected, separated into relevant and irrelevant forms, and processed into classification mechanisms able to categorize incoming new data in real-time. Location, time, and geographic parameters are among the most important indicators within these data spaces and among the most ancient. Maps, in fact, can be seen as powerful visualizations storing and conveying large amounts of geographic data, and geographic information systems were among the first problem domains for research in “Very Large Databases.” Moreover, geography research continues to create requirements and solutions for spatial and temporal representations in the next generation of Big Data systems. This course is an introduction to the field of Big Data research from a socio-technical systems perspective. It explains historical roots, social and economic application areas, as well as technical fundamentals. The area is explored along the dimensions of the “five Vs”: volume, variety, velocity, veracity, and visualization.

Details:

• Course number: GEOG 281
• Course title: The World and Big Data
• Term: Fall 2023
• Professor: Hui (Henry) Luan
• CRN: 15435
• Counts for DH Minor as: Lower-Division Elective

View this course in the UO Schedule.