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10 Bits: The Data News Hotlist

by Joshua New
Runway Model

This week’s list of data news highlights covers August 29 – September 4, 2015 and includes articles about a new artificial intelligence support system for first responders and machine learning algorithm that can predict the likelihood of a fashion model’s success.

1. Predicting Beijing’s Air Quality with Artificial Intelligence

Researchers at IBM are testing a system called Green Horizon that can predict the severity of air pollution in Beijing 72 hours in advance by combining and analyzing data from a host of different types of data, such as meteorological and environmental data. Green Horizon can identify specific areas where pollution will be worse with a resolution of one kilometer, which is 30 percent more precise than prior methods. Researchers are working to expand the program’s forecasting capacity to up to 10 days, as well as develop decision support systems to reduce polluting emissions.

2. Understanding Diabetes with Data

Google’s new life sciences division has partnered with French pharmaceutical company Sanofi to build better methods of collecting and analyzing data about diabetes to help patients better manage the disease. The partnership will combine Sanofi’s expertise in treating type 1 and type 2 diabetes with Google Life Sciences’ analytics capabilities and miniature electronics to incorporate connected sensors, data on glucose levels, and other information to develop new treatments and lower the cost of care.

3. Opening Autism Data to Researchers

Autism Speaks, an advocacy organization, has launched a web portal for its MSSNG database, which houses genomic information on people with autism and their family members, to make their data available to researchers and encourage knowledge sharing. The goal of MSSNG, which Autism Speaks hopes to populate with the genomes of 10,000 people with autism and their families, is to spur the development of breakthroughs that could provide insight into the cause of various subtypes of autism, as well as improve diagnosis and develop personalized treatments for the disorder.

4. Giving First Responders an Artificially Intelligent Partner

The National Aeronautics and Space Administration’s Jet Propulsion Laboratory, one of the agencies research arms, is developing an artificial intelligence system dubbed AUDREY to improve the situational awareness of law enforcement, firefighters, and other first responders. AUDREY, which stands for Assistant for Understanding Data through REasoning, Extraction, and sYnthesis, is designed to run on ordinary personal computers to help first responders quickly identify critical information in an emergency, such as hazards firefighters should be cautious of when responding to a fire in a particular building, as well as share data on body-worn cameras and sensors with dispatchers and commanders to help them make more informed decisions. Researchers hope AUDREY could be deployed in the next two years.

5. Finalizing the DATA Act

After over a year of deliberation, the Office of Management and Budget (OMB) has finalized a total of 57 data standards for government financial data required by the Digital Accountability and Transparency Act of 2014 (DATA Act). The standards had been open for comment on OMB’s GitHub page and pertain to data elements to be included on USASpending.gov to help track how the government spends its money. Though the standards have been finalized, OMB and Treasury Department officials have said they will periodically review and update these standards as needed to reduce the burden of reporting this data.

6. Calling for Government Support for the Internet of Things

A National Science Foundation report sponsored by the Semiconductor Research Corporation and Semiconductor Industry Association, a research consortium and trade association, respectively, has identified an urgent need for increased government funding for research and development to support the Internet of Things. The report outlines several areas of technology research, such as real-time communication systems and intelligent data storage, that should be part of a coordinated government initiative. Government funding of this initiative, the report argues, would help industry overcome some of the technical challenges posed by the Internet of Things and channel the economic and national security benefits of the technology to the United States, rather than other countries.

7. Reading Heartbeats and Health Records

The Food and Drug Administration (FDA) has approved a digital stethoscope called Eko Core that can integrate a patient’s heart sounds into his or her electronic health record. Eko Core records and wirelessly transmits heart sounds to a smartphone app, which can then integrate this data into health records to improve cardiac monitoring and documentation.

8. California’s Open Data Bill Fails

A bill in California’s Senate that would require the state to implement an open data policy and install a chief data officer has failed to pass. If the bill had passed, each state agency would have had to establish a data coordinator to work with the state’s chief data officer to establish benchmarks for publishing data on a statewide portal. The State Senate did not vote against the bill, but rather the bill failed to gain enough support for continued deliberation.

9. Opening More Medical Device Data

FDA has expanded its openFDA initiative, designed to open medical device data to the public, to provide access to current data on device classification, 24,000 registered device companies, and over 100,000 registered medical devices. Additionally, openFDA’s database now houses nearly 40 years worth of historical data on medical device premarket approvals, approval supplements, and clearances, as well as data on device recalls dating back to 2002, and adverse events dating back to 1991.

10. Machine Learning Models Take on Fashion Models

Researchers at Indiana University have developed a machine learning algorithm that can predict a fashion model’s likelihood of career success early on in their careers. The researchers analyzed data on 431 new female models with similar levels of modeling experience, including frequency of runway appearances, Instagram data such as the number of likes on their photos and the sentiment of comments, to train their algorithm, which was able to predict six of the eight models that would become popular at fashion week shows earlier this year. The researchers expect their findings, such as the heavy influence of social media activity on future success, will give some an edge in the fashion industry.

Image: Lover of fashion.

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