November 05, 2013, 3:47 PM — What if big data could do even more to help with world problems? So far, companies such as IBM, Google and HP have taken on immense challenges, from analyzing the number of cars that use a bridge on a busy highway or calculating how many people see one small ad in a Web browser. Google has even announced an ambitious project that will address human aging.
But several major world problems remain elusive. In some cases, the data is not available to analyze at all. In others, computers fast enough to process the data haven't been invented yet. Here are five problems worth tackling. Will any big data companies step up to the plate? We'll have to wait and see.
Health Records for the World: Medicine Where It's Needed Most
Most people have some semblance of an electronic health record (EHR), even if it's simply a notation about a recent health check-up. The tools and technology are in place to maintain a world health record repository, too. With a global database, pharmaceutical companies could develop the most-needed vaccines and medications - that is, the supply chain would be optimized for actual needs.
What's missing? Access to the global data. "Health records are kept in a whole bunch of disparate systems, and providers don't have an incentive to share them," says Mike Miller, co-founder at chief scientist at Cloudant, a distributed database provider. "Even if we had all the data in one place, we'd still need to optimize it all with machine learning algorithms and real-time analytics. That's the piece we're still working on today to get it right."
Human Brain Map: See How the Rest of the Body Works
A model of the human brain could help science immensely. Doctors could see how a tumor grows or which functions in the brain controls other organs in the body. New science initiatives such as Europe's Human Brain Project seek to build a brain simulator in the next 10 years.
The problem? The supercomputers required for that kind of processing will have to be 1,000 times faster than those in use today. There are millions and millions of neurotransmitters, all interconnected and processing "data" in the brain.
"This will require substantial developments away from conventional silicon chips onward to biological chips for molecular computing," says Oliver G. McGee, a former U.S. deputy assistant secretary of transportation for technology policy in the Clinton administration and a professor at Howard University. "Molecular computing has the vast potential of 750 times faster extensive data management than conventional silicon chip computing for rational-intuitive cognition mapping of our cranial-abdominal brains."
Map World Supply of Uranium: Track Weaponization, Energy Supply
As with any massive undertaking in collecting data at a global scale, tracking the world supply of uranium is at least plausible - that is, if all of the puzzle pieces fit together perfectly.
Keith Cooper, CEO of data collection company Connotate, says we've only addressed part of the problem, as some countries don't publicize all their supply records. "There are large stockpiles around the world that were enriched prior to the advent of the Internet and would have escaped reporting standards in place today." Fortunately, calculating the big picture isn't difficult, as countries using uranium for weaponization are small in number.
What really needs to be tracked in order to understand the global supply available, he says, is the 15% of enriched uranium that's the most valuable. "We would need to identify and track all activities related to the sale (black market or legal) and distribution of uranium via forums, blogs, regulatory bodies, statistics around it, production data and mining activity all reported from NGOs and government agencies. Some form of human and machine intelligence must be run against the corpus of results."
Real-time Global Crime Data: More Proactive Policing
Many local law enforcement agencies already have a wealth of crime data at their disposal. Police officers can easily access their database of crime records from the squad car and react to a suspect accordingly.
The problem? The data only includes past crimes, Cloudant's Miller says, not crimes that have just recently taken place or are even in process. Instead of responding to crimes as they occur, police are forced to serve a more reactionary mode.
But that's changing, Miller says. For example, police in Oakland, Calif. have set up acoustic monitors to identify gun shots. Technology called ShotSpotter then uses big data analytics to triangulate the location of a potential crime, and police are dispatched in real-time. The benefits of accurate, real-time crime data extend beyond law enforcement, too: The Trulia Local heat maps now show crime reports to help people buying a home choose a safe neighborhood.
Tracking Everyone's Children: Better, More Timely Amber Alerts
There are ways to report a missing child today, such as the Amber Alert system in the United States, but these notifications occur after the fact. The technology to track the current location of a child is already here. Many smartphones can send a child's location to a parent using a service such as Google Location Reporting (formerly Google Latitude). Meanwhile, Volkswagen's Car-Net and Ford's MyKey apps can report when teen drives leave a specific geofenced area.
What's missing? Analytics. Jaison Manian, a vice president at digital marketer Roundarch Isobar, says predictive technologies could help. A big data company could analyze a child's behavior patterns, as long as parents are willing to share that data, of course.
"Predictive analytics can track deviance from everyday movement patterns and immediately send an alert to the parents," he says. If there's cause for alarm, an alert would be issued in real-time - rather than hours later, when it might be too late.
John Brandon is a former IT manager at a Fortune 100 company who now writes about technology. He has written more than 2,500 articles in the past 10 years. You can follow him on Twitter @jmbrandonbb. Follow everything from CIO.com on Twitter @CIOonline, Facebook, Google + and LinkedIn.
Read more about big data in CIO's Big Data Drilldown.