This week’s list of data news highlights covers November 14-20, 2015 and includes articles about a new app that uses IBM’s Watson to make holiday shopping easier and the launch of the European Union’s open data portal.
The European Union has officially launched its open data portal, which has been in beta form since 2012, to make it easier for citizens, businesses, journalists, and governments across Europe to access and use government data. The portal already contains 240,000 data sets from 34 countries and the team that developed the portal expects it to grow substantially. In a study released with the announcement of the launch, researchers estimate that Europe’s government data is just 44 percent open. As this percentage increases, the study indicates the value of open data in the EU will reach €75.7 billion ($80.6 billion) by 2020.
Researchers at Brown University have developed a robotics system that can learn to pick up unfamiliar objects and then teach other robots to do the same. The researchers first taught a Baxter robot, a common type of research robot equipped with grabbing arms, cameras, and infrared sensors, to examine objects and determine potential ways to pick them up. The robot then tests these methods to identify the most reliable approach and shares the results with other robots. The researchers note that by sharing solutions, the 300 Baxter robots in laboratories around the world could learn how to grasp one million different objects after just 11 days.
IBM has created the Watson Trend smartphone app, which relies on the Watson cognitive computing platform to help users identify the trendiest products of the holiday season, learn why these products are popular, and determine the best time to buy them. Watson Trend analyzes data about products from 10,000 sources, such as social media, ecommerce websites, online reviews, and blogs, and identified the 100 most popular products in the categories of consumer electronics, toys, and health and fitness. Watson Trend will eventually incorporate geographic and language data to help users develop more personalized lists based on user preferences.
U.S. Congressional Representatives Dave Brat (R-VA) and Seth Moulton (D-MA) have introduced the Statutes at Large Modernization Act to require the National Archives and Records Administration to publish the Statutes at Large—a sequential list of all U.S. federal laws and regulations—in an open and machine-readable format. The Statutes at Large is publicly available but only in PDF and text-based formats, which makes it difficult for computers to search and manipulate this data.
The National Aeronautics and Space Administration’s Jet Propulsion Laboratory (JPL) is developing a network of 200 space-based sensors called FireSat that can rapidly detect fires on earth and notify emergency responders. FireSat will be able to detect a fire 15 minutes after it grows between 35 to 50 feet wide and transmit low-resolution images of the fire with its longitude and latitude coordinates at a rate of once per minute, substantially more frequently than existing satellite-based fire detection systems, which can only transmit images twice per day. JPL plans to have FireSat fully operational by June 2018.
Canadian online retailer Shoes.com has partnered with artifical intelligence company Sentient to develop an artificial intellgience system that can analyze images to help users more easily find what they are shopping for. Users can identify their preferred type of shoes from images and the system will provide more results based on its analysis of other visually similar shoes. Shoes.com expects the new system will help users find exactly what they are looking for faster than traditional recommendation tools, as it relies on a customer’s specific stylistic preferences instead of factors such as brand recognition.
The U.S. National Institute of Standards and Technology (NIST) has announced the winners of its Reference Data Challenge, an app development challenge to develop new methods of using NIST Standard Reference Data (SRD) with mobile devices. SRD includes a broad range of scientific and technical data sets useful for a variety of scientific disciplines . The winning app allows users to quickly access SRD by tapping a smartphone against a near-field communication tag to automatically send a particular data set to the phone, minimizing workflow interruption and making it easier for researchers working together in a lab to share relevant data with each other.
Genomics company Illumina has partnered with the Hartwell Autism Research and Technology Initiative (iHART), which develops autism-research tools for the scientific community, to build a genomic database for autism spectrum disorder. iHART will house 5,000 genomes of individuals with autism and their families in Illumina’s cloud-based genomics analysis platform, which will make it easy for researchers to easily access and analyze this data to study genomic variations associated with the disorder. The genomics database is part of iHART’s larger effort to build the largest open access database of bioinformatic data related to autism.
An artificial intelligence system developed by Japan’s National Institute of Informatics has earned a passing grade on Japan’s college entrance exam, scoring 511 out of a possible 950 points, beating the national average by 95 points. The system is adept at math and history-related questions, though it scored below average on questions that required greater language processing abilities. The Institute has been training the system since 2011 and managed to achieve a passing grade on the exam well ahead of its initial goal of passing the test by 2021.
Startup incubator Prospect Silicon Valley and Forschungsgesellschaft Kraftfahrwesen mbH Aachen , a German automotive technology organization, have developed the “Driving Simulator and Vehicle Systems Lab” (SimLab) in San Jose, California, to help spur the development of autonomous car technologies. SimLab simulates real-world driving scenarios to make it easier for startups to test their technologies without having to develop costly real-world experiments. Startups working with SimLab can record every action taken by a test car in the simulated environment and use this data to refine their products to ensure they are reliable enough for use on the road.