This week’s list of data news highlights covers October 25-31 and includes articles about a catching tax dodgers with big data and an Oxford University project to build a human genome database.
The Great Elephant Census, launched by Microsoft cofounder Paul Allen in partnership with Botswana nonprofit Elephants Without Borders, is attempting to count Africa’s elephants to strengthen conservation efforts. A team of researchers is testing new technologies that can help track and protect savannah elephants, such as drones and image recognition technology, in addition to small aircraft flyovers, to overcome limited resources and manpower. With accurate population data, the team believe that policymakers can better fight poaching and researchers can better understand elephants as a species.
Google X, Google’s research and development unit, is working on a project that combines disease-detecting nanoparticles and a wearable biometric sensor to diagnose cancers, impending heart attacks, strokes, and other medical problems. Researchers hope that using nanoparticles for real-time monitoring can pave the way for significantly faster diagnosis and intervention by healthcare providers. Early diagnosis is crucial to treating certain diseases that are currently only detectable after they have become untreatable.
The Indian Government has released a draft of its plan to boost the IoT industry in the country and help tackle problems in agriculture, health services, energy, and disaster management, among other areas. Proposals in the policy include water quality monitors in taps and reservoirs, as well as biometric monitors that can detect changes in health metrics and send alerts to hospitals. The plan aims to increase the amount of connected devices in India from 200 million to 26 billion, creating an IoT industry worth $15 billion by 2020.
Democrats and Republicans are relying on voter information databases, data analytics tools, social media, and other big data tools to gain a competitive edge in the mid-term elections. President Obama’s election in 2012 was widely credited to his campaign’s early adoption of these technologies, but the Republican National Committee is fighting to catch up. Both sides are trying to leverage technology advances in data-driven voter targeting, such as mapping software, poll monitoring programs, and social media analysis, to increase turnout in the mid-term elections, which have notoriously low voter participation rates.
IBM and Twitter have announced plans to combine the former’s data-analysis business, which includes its Watson AI technology, with the latter’s database of billions of tweets. Twitter and IBM say the goal of the partnership is to enrich business decision-making by monitoring and analyzing what the world thinks in real time. Twitter’s vice president of data strategy says that Twitter’s information resource, combined with IBM’s analytic power, could have nearly limitless business applications, even beyond traditional applications like marketing and product development.
An automatic data-sharing accord between the U.S. and the five largest E.U. economies has now broadened to include more than 50 countries and territories. The accord is designed to capture lost tax revenue from overseas banking activities that have previously gone under the radar due to the lack of international cooperation. All countries involved in the pledge have committed to start exchanging data by 2018. Holdouts have been encouraged to participate in the effort to reduce bank secrecy, which is estimated to cost billions of dollars in lost tax revenue every year.
A 20-week pilot study using five years worth of police data is helping London police identify gang members that have the highest risk of committing crimes. The software, developed by Accenture, mines police intelligence, social media data, and known criminal history to establish a risk assessment model to forecast the likelihood of gang members committing violent acts. The goal of the program is to use predictive analytics to help the police focus their limited resources on where they would be most effective.
Microsoft has added new functionality to its cloud computing platform Azure to prepare it for the Internet of Things. The new services are intended to help with processing data from the multitude of networked devices and sensors in the IoT, as well as manage the data collected from hybrid environments, where some data sources reside in the cloud and some are on-premise. Microsoft hopes this increased functionality will enable Azure to tackle the problems associated with structured and unstructured data sources that feed into the platform from across multiple locations—problems that will only be compounded as the Internet of Things allows for increased data capture and inputs.
Oxford University is partnering with the U.S. based Chan Soon-Shiong Institute of Molecular Medicine to use IoT devices and big data to sequence the genomes of individual patients at the UK’s National Health Service. The project, which will rely in part on networked biometric monitors, aims to sequence the genomes of 100,00 volunteers and integrate the information with clinical data to improve patient care and pave the way for targeted, more precise medicine. The infrastructure being developed by the project is expected to reduce the time needed to examine a patient’s genome from 11 weeks to potentially just seconds.
As part of Germany’s public-private “Industrie 4.0” partnership, the 1,000 manufacturing units in Siemens AG plant in Amberg, Germany have been set up to communicate with each other and assemble components without human input. The plant is one of the first fruits of the efforts of the German government, companies, universities, and research institutions to modernize German manufacturing with networked smart factories. Germany hopes the integration of the Internet of Things (IoT) into its industrial manufacturing sector will help maintain its edge as Europe’s largest economy.