Five Things to Know About Data and Society at Columbia

data brains editedData. It’s everywhere. We are living in a time of unprecedented data generation: from the photos we take on our smartphones to the temperatures registered on the office thermostats— it’s all data. This trend is universal and unstoppable, as data are revolutionizing the very way in which we live, work, and think.

Read on to find out more about how data analytics is changing the research paradigm, and how Columbia researchers are harnessing the power of data.

1. How is “Data and Society” a Big Idea at Columbia?
It is Columbia’s response to the “data deluge” of our time, involving University-wide research, scholarship, and teaching of data science and analytics to address today’s issues.

2. How are Columbia researchers harnessing the power of data?
Faculty across Columbia are using data analytics as the starting point for their research. By discovering patterns that could not be seen using traditional research approaches, data analytics allows faculty across all schools and units to ask completely novel questions in their fields of research, whether unlocking autism trends, understanding freshwater scarcity, or managing patient information to improve clinical decision-making.

3. How do data analytics change the way research is conducted?
Traditional scientific method requires the researcher to pose a hypothesis (the “research question”) and then construct a series of experiments to test that hypothesis. Data analytics methods start with the data, apply one or more algorithms to the data, and then examine whether patterns emerge that might lead to interesting research paths. “Listening to the data” leads to complex questions that can then be advanced by the researcher in ways that accelerate the whole knowledge-creation process.

4. What is the Data Science Institute?
With more than 150 faculty working in a wide range of disciplines, the Institute seeks to foster collaboration in advancing techniques to gather and interpret data, and to address the urgent problems facing society. Watch the video.

5. What are some examples of how “listening to the data” has led Columbia researchers to new frontiers of knowledge and discovery?

bearman_150pxPeter Bearman on autism
Peter Bearman, the Jonathan R. Cole Professor of the Social 
Sciences, studied the population level drivers of increased autism prevalence. Learn more



FB2403_Bowman_1DuBois Bowman on the progression of disease
DuBois Bowman, chair and professor of biostatistics, Mailman School of Public Health, is analyzing health records and brain scans using novel automated tools to try to understand how neurological disorders like Parkinson’s progress over time. Learn more about Professor Bowman.


Augustin Chaintreau on geotagging and identifying users of social media 
Augustin Chaintreau, associate professor in the computer science department, was part of a joint study with Google revealing that geotagged posts on just two social media apps are enough to link various accounts held by the same person. Read the BuzzFeed article.


Patricia Culligan on trees and stormwater management in New York City
Patricia Culligan, professor of civil engineering and mechanics, the Fu Foundation School of Engineering and Applied Science, partnered with the Mayor’s Office to analyze New York City’s massive data set on plantings around the city to understand the role that the city’s
trees play in street-level water management. What’s the difference between
a tree that drinks up rainwater and one that doesn’t? List
en to this interview with Professor Culligan and find out. 


Ppeter-demenocal-300eter deMenocal on climate change
Peter deMenocal, director of the Center for Climate and Life and professor in the department of earth and environmental sciences at the Lamont-Doherty Earth Observatory, says “the climate problem, broadly writ, is a data problem.” Learn about the Center for Climate and Life here

Screen Shot 2016-04-19 at 4.05.31 PMLucius Ricco on pothole prediction
Lucius Ricco (aka Professor Pothole), senior lecturer in discipline at Columbia Business School, used data analytics to calculate to what degree bad weather and bad management contribute to New York City’s potholes. Read The New Yorker article.