Instead of searching through multiple data sources that are often incomplete and difficult to access, you can simply go to the Data USA website to answer your questions. Data USA provides a mobile-friendly and easy-to-use platform that, through algorithmic reporting, turns numbers into knowledge. It’s a free portal that allows millions of people to conduct their own analyses about the U.S.–its people, places, industries, skill sets, health, and educational institutions.
Data USA aims:
There have been previous data visualization engine projects but none are so broadly scoped and comprehensive, or user-friendly and visually pleasing as Data USA. In 2014, Deloitte (which became a Media Lab member in 2011,) Datawheel, and César Hidalgo, director of Collective Learning at the MIT Media Lab, met to define the scope and timeline of the Data USA project. Then together they discussed the available data sources, the data sets to be included in the platform, and the design. The team—comprised of economists, data scientists, designers, researchers, and business executives—worked for more than a year with input from policymakers, government officials, and everyday citizens to develop Data USA. And the work goes on: The Media Lab’s Collective Learning group is currently collaborating with Deloitte on building an update of Data USA.
Data USA is among the most comprehensive visualization engines for shared U.S. government data to date. It aggregates and visualizes publicly available data from multiple U.S. sources, including the Department of Labor, Department of Commerce and Department of Education. Through advanced data analytics and visualization, the easy-to-use platform allows all users to browse and filter information and then create visualizations to enhance their understanding of national, regional and local issues, reveal patterns, and make more informed decisions about your life, your career, and your community.
Here’s how it works: Let’s say you want to investigate where you live, or want to live–just type the location in the Data USA search box. Within seconds, a page will open with topline statistics for that community’s population, median household income, and median age. You can then delve more deeply, via a menu of options that are labeled about, economy, demographics, education, housing & living, health, and safety. Each choice will lead you to detailed numbers, percentages, and graphs, plus some analysis, all broken down by specific issue or factor. You can follow a similar path of data exploration for industries, occupations, and education.
Data USA puts public U.S. government data in your hands. And it is an evolving resource: The code is open source, and the platform is scalable. Usage and search patterns over time will drive new areas of exploration and thus lead to platform updates.
See the project website
Ann Perrin of Deloitte speaks about the diversity of skills on the Data USA team:
“Collaborating with César and his team at the Media Lab has been a great, great experience. We spent a lot of time exploring our mutual interests and discussing what has no become Data USA. And I think that it has been fantastic to see students, policy makers, government officials, executives using Data USA so actively.
To me, one of the biggest critical success factors of this project was the diversity in skill set around the table. So we had people that knew the data inside and out. We brought economists to the table who’d worked at Commerce [US Commerce Department] and knew U.S. government data and what you could actually do and how you could crosswalk it. Then we had individuals who had deep data science expertise and deep design and UI [user interface] expertise. So I think ultimately it came down to, really, the synergies of that in order to make those decisions.
And so, all of the things together have made it really very gratifying and certainly exceeding expectations, and it’s something that we hope to build upon. So we’re working on Data USA 2.0.”
César Hidalgo of the MIT Media Lab, talks about the value in collaborating with Deloitte on Data USA:
“When you work in collaboration with a company like Deloitte, in this case, you realize that they’ve been talking to a group of people that is very different, that see these things very differently, and that have a different set of concerns and set of applications. And in that context you get a lot of ideas, and I’m sure that it goes both ways, you know.
Also, what I like about working with them is that they’re really good team players. And to get us to make something sophisticated, you have to work with a group of people that are willing to put their egos aside and they know how to do it. Because if there’s people that are too concerned about, like, ‘This is my thing. I don’t like that because that was your idea…’ then a large, collaborative project doesn’t work. And, in this case, I thought there was basically none of that.
You know, sometimes we would disagree on things. But when we would disagree on things, always I thought those disagreements were solved in a way in which it was clear that people had the benefit of the product and the project as their primary concern. And that’s, I think, why it was so good to work in this collaboration because it was really like good, smooth teamwork.”
Anne-Ruxandra Carvunis, Thomas Rolland, Ilan Wapinski, Michael A. Calderwood, Muhammed A. Yildirim, Nicolas Simonis, Benoit Charloteaux, César A. Hidalgo, Justin Barbette, Balaji Santhanam, Gloria A. Brar, Jonathan S. Weissman, Aviv Regev, Nicolas Thierry