Facebook launched an official research program in 2009, giving the academic community tightly controlled access to a ballooning set of granular data about social interactions and activity. It quickly became a “holy grail” for social scientists, who have been drawing on it to publish important new findings almost daily. The question now is whether this kind of scientific research will end up being curtailed in the continuing backlash against data-sharing of any sort.
Day two of the Facebook CEO’s grilling in Washington, DC, was more aggressive than the first. It gave us a glimpse into what Facebook has done in the past, where it currently stands, and where it is heading next. Here are some of the key points to emerge from his testimony.
The tried-and-true credit hour is so entrenched in higher education, it’s hard to imagine a system that doesn’t measure students’ academic progress in units of classroom time. Generally speaking, if a student reaches 120 hours, he or she will be walking across the stage to claim a bachelor’s degree. But the conversation around learning outcomes is changing, in part because of new technology-supported capabilities.
U.S. v. Microsoft, which hinges on a law passed decades before the modern internet came into existence, could have broad consequences for how digital communications are accessed by law enforcement, and for the nearly $250 billion cloud-computing industry. "The case is hugely important, it has implications for the future of the internet," says Jennifer Daskal, a former Justice Department official who now teaches at American University Washington College of Law.
Data has permeated higher education in a lot of different ways. Experts have emphasized the continued need to analyze data to determine the success of programs and initiatives. But with the Internet of Things advancing into a variety of aspects of campus life, higher education institution stakeholders now have an immense amount of data at their fingertips, which can be drawn from to make better decisions.
Businesses increasingly rely on data analytics to inform everything from daily operations to customer service to marketing initiatives. As a result, data science has become a hot skill in high demand across a broad range of industries. And bootcamps are great way to hone data science skills, get up to speed on the latest data science trends, shift your career path or create greater job security within your industry.
Gilberto Titericz, an electrical engineer at Brazil’s state oil company Petrobras, told his boss he planned to resign, after seven years maintaining sensors and other hardware in oil plants. By devoting hundreds of hours of leisure time to the obscure world of competitive data analysis, Titericz had recently become the world’s top-ranked data scientist, by one reckoning. Silicon Valley was calling. “Only when I wanted to quit did they realize they had the number-one data scientist,” he says.
No matter how the case is decided, there are potential negative implications for U.S. competitiveness. If the court supports the use of search warrants to obtain data stored abroad, it will feed the perception that the best way to protect data from the prying eyes of the U.S. government is to store it abroad with a non-U.S. provider. On the other hand, if the court rules that search warrants cannot be used overseas, foreign governments may try to force companies to store data within their borders to make it impossible for U.S. officials to execute a search warrant. This also damages U.S.
University of Washington (UW) researchers have developed a low-cost, long-range data-communication system that could make it possible for medical sensors or billions of low-cost “internet of things” objects to connect via radio signals at long distances (up to 2.8 kilometers) and with 1000 times lower required power (9.25 microwatts in an experiment) compared to existing technologies.
The National Science Foundation (NSF) today (8/24) announced $17.7 million in funding for 12 Transdisciplinary Research in Principles of Data Science (TRIPODS) projects, which will bring together the statistics, mathematics and theoretical computer science communities to develop the foundations of data science. Conducted at 14 institutions in 11 states, these projects will promote long-term research and training activities in data science that transcend disciplinary boundaries.