For this talk, I will discuss about how I collected, analyzed, and visualized real-time civic data from open data sources and APIs. As part of a fellowship with Stamen Design and Gray Area Arts Foundation last year, I created a project called Urban Heartbeat. My work explored civic, social, and environmental data at the neighborhood level. I collected and analyzed data from June to August 2015 and analyzed the data in a series of experiments. I performed spatial and content analysis of social media to discover the location of people’s activities in the neighborhood. I used data from DataSF.org, Instagram, Twitter, Foursquare, NextBus, Waze, Factual, Weather Underground, Craigslist, and other sources. The technology used in this project includes D3.js, Firebase, CartoDB, and Node.js (including Node libraries for color analysis and image quantization; geospatial analysis, network analysis, natural language processing, sentiment analysis, and machine learning). The resulting artwork was a generative data installation at the Grand Theater in San Francisco’s Mission District. The art allows passersby to explore their neighborhood via visualizations at the urban scale. My project work has been exhibited in Geneva, Bangalore, Pittsburg, and is currently on display in San Francisco. In 2016, my work has continued and I’m partnering with architects and urban planners in the Bay Area to analyze urban space, make planning decisions, and engage with local communities.