NYU Data Science newsletter – June 8, 2015

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NASA has a lot of data.

Understatement, right? In pursuit of its exploration mission, NASA has generated, collected and compiled a vast amount of data through the eyes of satellites, telescopes, robots, spacecraft, wind tunnels, laboratories and the cameras of astronauts that has helped us better understand Earth, other planets, and the depths of space. In the time it took you to read this sentence, NASA gathered approximately more than 2 gigabytes of data from our nearly 100 currently active missions. And that’s just the current remote sensing data flow.

In popular conversation, discussions of data visualization often involve specialized interactive graphics – typically intended to convey a story – that were hand-crafted by skilled designers. Over our years working in visualization, a central goal of our group has been to build tools that help designers craft sophisticated graphics, leading us to create tools such as Prefuse, Protovis and D3.js.

In the grand scheme of things, however, finely honed hand-coded visualizations are the exception, not the rule. Instead, the vast majority of the world’s visualizations are produced using end-user software, most notably spreadsheet applications. While valuable, these tools are often created by engineers, who, though well-intentioned, unfortunately lack familiarity with effective visualization design and how to support the iterative process of data analysis. Better tools are needed to help everyone, not just skilled designers, create effective visualizations and better understand their data.

The Milky Way has been weighed to its most accurate level yet – and the results could help define how wide it really is.

Previously, the mass of our galaxy had been estimated by observing the speed of stars, but it had a huge margin of error.

The latest result, though – said to be the most accurate and made using a new method of measurement – shows the bulk of our galaxy is 210 billion solar masses.

One of the big themes from Health Datapalooza this week was the push to develop better ways to visualize data to make data streams more manageable, contextualized and make it easier to develop insights.

Health Data Consortium launched an obesity data challenge in the U.S. and England. The U.S. competition will collaborate with deBeaumont Foundation to attract visualization tools that help healthcare professionals and health official work with patients to reduce obesity. The NHS will preside over the challenge in England.

The era of Big Data—of increasingly vast streams of information generated by people and their devices—is raising thorny questions for city planners.

To hear some boosters describe the benefits, you might suppose Big Data is about to unleash an unqualified urban renaissance. We’ve all heard the claims: Sensors will eliminate traffic jams and optimize energy demand. New mapping technologies will identify, and help to correct, urban problems no one could see before. Social media and crowdsourcing will target big and little problems, down to which potholes to fix—maybe even make governments work again.

As these claims have inevitably failed to live up to their hype, a pronounced backlash has set in. Big Data, and its cousin the Smart Cities movement, are both increasingly dismissed as fads and technology marketing schemes—and worse for some, examples of a too-reductionist science gone amok. The charges are worth considering.

… According to Damon Davis, the director for the health data initiative at HHS, HealthData.gov is a catalog of health, social services and research data made available to the public to improve the country’s health.

The relaunch includes user-friendly tools and updates the platform’s underlying technology for more efficient performance, Davis said in a blog, in an effort to nurture more applications, products and services capable of enhancing health care.

The project started with the migration of the catalog content to the DKAN open data and open source platform, which is the same technology used by Data.gov.

The robots are fighting it out at a Pomona, California fairground this weekend, and the winner might someday save your life.

Machines developed at the Massachusetts Institute of Technology (MIT) and Worcester Polytechnic Institute (WPI) are facing off against nearly two dozen steely rivals from the US, Europe and Asia in a contest sponsored by the Defense Advanced Research Projects Agency (DARPA), the US military research program that helped develop the Internet. The goal of the two-day contest, which wraps up Saturday night, is the creation of rescue robots that can operate in dangerous environments — burning buildings, for instance, or damaged nuclear power plants.

The winning team earns bragging rights as a global leader in robot technology.

Which top Masters Courses should you consider for a great career in data-science?

A frequently cited study by McKinsey predicts that by 2018, the United States could face a shortage of 140,000 to 190,000 “people with deep analytic skills” as well as 1.5 million “managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

The field is so hot right now that Roy Lowrance, the managing director of New York University’s new Center for Data Science program says “Anything that gets hot like this can only cool off.” Regardless of this, the current school year won’t be over for another five months and 50% to 75% of its students already have firm job offers!