It's called the Twitter Decahose, and it's a massive dataset that charts one-tenth of all the messages flowing through the social network. Researchers at MIT used that data to illuminate a 3D printed model of the school's campus.
As a point of reference, the Decahose streamed something like 1.5 billion tweets from 71 million individual users over nearly 30 days in 2012. That's 38 million tweets a day, and that's big data indeed.
The team at MIT used this geolocated data as fodder for their LuminoCity model and it's their contention that such models could be used for a variety of purposes in urban planning and real-time reporting of the hive mind.
Designed by Vijay Gadepally and Zachary Weber of the MIT Lincoln Laboratory, the model is a projection of the geotagged data points up through the bottom of the model.
This 3D printed map of the MIT campus includes a group of sensors and a computer interface, called CLAIRITY, which was configured to illuminate nodes according to various data inputs like air quality.
Weber, one of LuminoCity's developers, said the map has presented time-lapse visualizations of CLAIRITY raw data and that it has already found applications in data research at MIT. Over the summer, LuminoCity helped student researchers visualize gas and particulate levels taken from sensors located around campus.
The CLAIRITY network which drives LuminoCity continuously transmits data through a wireless connection to a central computer.
The developers says they envision a scenario where data sets could be mined to provide administrators at MIT a picture of breaking key-word searches and topic clustering where Twitter traffic volume might reveal useful insights into campus patterns and activity. Weber and Gadepally say their idea might be radically scaled up to reflect a visualization of a whole city and used to provide information about traffic patterns and mobile phone use.
The MIT team says 3D printing ushered in a revolutionary way to interact with big data, and using a 3D printed mockup up of a physical or conceptual environment allows them to display data on the model to reflect real-time data patterns.
They says it's the ability of models like LuminoCity to provide shared, tangible 3D visualization to teams of researchers and planners which gives the idea its power.
The model might be used like this: Say the traffic manager of a major city needs to work with an urban planner and utility company personnel to investigate traffic patterns in a crowded neighborhood. The team could then take data derived from sensors which monitor traffic lights, social media, street cameras and mobile phones to identify and alleviate traffic hot spots.
The PDF version of the paper is available here.