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Big Data Visualization and Society - Riyadh
COURSE CONTEXT
The course taught students to work with “Big Data” to answer or expose urban issues. Students learned the technical skills involved in working with “Big Data”. Following the overall project’s objectives, the class focused on transportation networks, and more specifically the public policy and social implications of the creation of the future metro system in the city of Riyadh. With the introduction of the metro system, students reflected about their implications in the social dynamics of the city, considering the existing gender and
racial inequality, the overall design of the transportation network and their local issues, the implications of new technologies and transportation modes in the city, and civic engagement in transportation planning, among others. Through the projects, students aimed to develop projects capable of trough design, facilitating the conversations regarding transportation policy between citizens, policy-makers and stakeholders.
Technical Sessions
• Open-source development – Github • Python • Data wrangling: Pandas • Web-scrapping • Network Analysis • Web-development: HTML, CSS
• JavaScript • Data-structures • D3 • Data-driven Maps • User interaction
Datasets Used
• 30+ Gigabytes of data collected over 3 months • Taxi trips from taxi operators (e.g., Uber and Easy Taxi) • Taxi trips from crowd sourced mobile phone applications • Riyadh bus routes (ADA) • Existing bus demand • Tweets: 8 gbs of geo-located tweets 2+ months of data collection
• Foursquare Check-ins: 1 gb of trending venues check-ins 2+ months of data collection • Instagram: 1 gb of geo-located instragram posts 2+ months of data collection • Google Points of Interest: 6,000 + POIs • OD Flows: Aggregated Flows Among Towers 24 hr Range • Road Network Congestion: Aggregated Network Flows