This week’s list of data news highlights covers May 21-27, 2016 and includes articles about a new Google project to make smart clothes and China’s plans to expand its market for artificial intelligence products and services.
The White House has released its Federal Big Data Research and Development Strategic Plan to guide federal agency research and development (R&D) initiatives related to big data. The plan outlines seven strategies for future agency R&D efforts that focus on addressing key opportunities and challenges, including increasing data science education and training, fostering collaboration between government, the private sector, academia, and civil society, and increasing the value of data with policies that promote data sharing and management.
Google has announced a partnership with clothing company Levi Strauss called Project Jacquard to develop clothing with conductive fabric woven in, allowing garments to serve as a platform for interaction with connected devices. Project Jacquard uses yarn that can conduct electricity, making it touch sensitive, to control applications on a wearer’s smartphone such as navigation and music apps. The goal of Project Jacquard is to produce smart fabrics on an industrial scale to encourage consumer adoption, and the first product—a denim jacket—will be available to developers and for retail sale in spring 2017.
Representatives Rob Latta (R-OH) and Peter Welch (D-VT) have launched a working group devoted to improving members of Congress’ understanding of the Internet of Things. The bipartisan working group consists of 19 members of the House Energy and Commerce Committee and will focus on educating members about the Internet of Things, identifying benefits and challenges for stakeholders, exploring the ideal role for the federal government to help grow the technology, and investigate the potential for public-private partnerships. The working group will produce a report by the end of 2016 detailing their activities and findings.
Tesla is using data collected from sensors in its customers’ cars to advance its efforts to develop self-driving car technology, allowing the company to access large amounts of real-world data rather than conduct its own field testing. In 2014, Tesla began installing a suite of 12 ultrasonic sensors in its vehicles to support emergency braking and its new autopilot features, as well as stream this data to Tesla engineers. With this approach, Tesla collects one million miles worth of data every 10 hours and can rapidly evaluate new autonomous features it installs in customers’ vehicles.
The city of Los Angeles has partnered with research group Corporation for Education Network Initiatives in California (CENIC) to provide researchers, academic institutions, and students with free, high-speed access to city databases to promote smart city research. Los Angeles already publishes over 1,000 data sets online, but through this partnership, the city will link its databases to the California Research and Education Network (CalREN), a 100 gigabit-per-second data sharing portal that will allow researchers to work with this data more quickly.
Mobile technology firm DMI has developed the Enterprise Interment Services System (EISS), a data management tool to improve oversight of U.S. veterans’ grave sites, many of which have been the subject of high-profile controversies in recent years due to poor record keeping. EISS allows grounds teams to match burial record data with geotagged photographs of each grave site to improve record management and comprehensively map grave sites. This approach could help avoid scandals such as how Army investigators in 2010 found over 100 unmarked graves at Arlington National Cemetery and multiple graves not appearing on official maps.
China’s National Development and Reform Commission announced a series of efforts to grow the Chinese market for artificial intelligence products and services to $15 billion over the next three years. The efforts will focus on advancing research related to core artificial intelligence technologies, provide financial support, and develop projects centered on robotics, smart homes and automobiles, and wearable devices. The efforts are an extension of China’s Internet Plus strategy, announced last year, to fuel economic growth by promoting the development of cloud computing, the Internet of Things, and other data technologies.
Google has announced plans to implement its new Trust application programming interface (API) to replace passwords as a means of securing mobile Android apps. Rather than simply verifying a password, Trust API runs in the background of a smartphone and analyzes a variety of data from the device’s sensors to develop a “trust score” that can more reliably indicate a user’s identify. For example, Trust API can use facial recognition, analyze typing patterns, and monitor a user’s gait to determine a trust score. If this score falls below a certain threshold, Trust API will prompt the user for additional verification.
The White House has released its Data Security Policy Principles and Framework for the Precision Medicine Initiative (PMI) to provide guidance for health-care organizations to responsibly use patient health, environmental, and genetic data to develop personalized medicine. The framework establishes eight core principles for PMI data, including the importance of ensuring participating organizations have high standards for data integrity and share their findings.
European airline company easyJet is developing shoes called Sneakairs that rely on Bluetooth connectivity, small vibrating motors, and smartphone navigation services to help wearers navigate unfamiliar environments. Sneakairs pairs with a smartphone app that uses the Google Maps API to help wearers plot their route and track their location. When a wearer approaches a turn, Sneakairs will vibrate in the left or right shoe to indicate which way he or she is supposed to go. Sneakairs could help tourists explore new cities but also offer potential for people with vision impairments to easily navigate their environment.