Look, up in the sky! It’s a bird, it’s a plane, no – it’s an Amazon drone!
Admittedly, Amazon Prime Air’s unmanned aerial vehicles in commercial use are still a little ways off. But such technology – along with other recent innovations, such as the use of unmanned aircraft in crop-dusting or even Department of Homeland Security border applications, or future capabilities to extend the notion of auto-piloting in passenger airplanes using autonomous machine logic to control airspace and spacing between planes –needs to be accounted for in terms of its impact on the air space. The Next-Generation Air Transportation System is taking on the change in the management and operation of the national air transportation system.
And semantic technology, natural language processing, and machine learning, too, will have a hand in helping out, by fostering collaboration among the agencies that will be working together to develop the system, including the Federal Aviation Administration, the U.S. Air Force, U.S. Navy, and the National Aeronautics and Space Administration, under the coordination of the Joint Planning and Development Office. These agencies will need to leverage each other’s knowledge and research, as well as ensure – as necessary – data privacy.
Security and collaboration vendor Securboration is the contractor to the federal government manning the project’s requirements to collaborate on policy, architecture and R&D activities. Semantic and related technology has a role here, says CTO Josh Powers, for “analyzing lots of structured and unstructured data and aligning it across the different communities.” Departments may put different names to the same equipment: The FAA, for instance, may call an empty aircraft flying over a region that is remotely piloted by someone in another region an unmanned aircraft system (UAS), or a drone, while the Air Force may call it a remotely piloted vehicle, or RPV. “Using semantics is an excellent way to align multiple vocabularies, and communities,” Powers says. “They don’t have to speak the same language but can all mutually understand” each other.
Instead of having dozens of third-party analysts manually try to connect the dots among how different agencies refer to the same items, Securboration is helping reduce that number – and the costs that would go with it – by leveraging NLP and ontologies to support the interoperability and sharing of information at the policy or R&D level. Getting the vocabulary right across agencies is important as higher-level policies for portioning out air space are refined. And, in forums where agencies need to understand and review each others’ data, they can turn to that mediation. “If I am an Air Force guy looking for what I think of as an RPV, I don’t have to perform 10 different keyword searches over different data sources to get all the information that fits what I need,” whether or not another agency’s documents refer to the same object as an RPV, he notes.
While the Next-Generation Air Transportation System has been around for a few years and is still many years away from being fully completed, “the work we are doing, which is just a small piece of the bigger [some $40 billion-big] project, is happening now,” says Lowell Vizenor, director of semantic technology at Securboration. “We are already starting to deliver value on that piece today to facilitate the work to be done to achieve the next generation system.”
Linked Data may have a role in the work Securboration is undertaking around processing policy documents. “We’ve been in discussions with director level personnel at the JPDO who represent the different stakeholders and gave them a Linked Data presentation,” Vizenor says, adding that they are very excited about it and publishing more structured data on their web sites in the form of microdata or RDFa Light, although it’s not currently funded work.
Securboration’s past has included work at the US Transportation Command, which is responsible for logistics and transportation of goods, services, and war fighters, through different operating areas, and its introduction there of the use of Linked Data and semantic reasoning over a very large architecture, Powers notes, resulted in the reduction of the response time between getting a request for a transport service and fulfilling it from two months to two weeks.
Those kinds of returns, the company thinks, will catch the eye of more customers and sectors as Vizenor, who’s new to the job, takes on the charge of bringing the capabilities Securboration is showcasing in its work with the Next-Gen Air Transport System to more real-world opportunities. Healthcare, for instance, is ripe, with all the changes underway with Oamacare and the need for various parties in the healthcare chain to communicate to each other, even if they express the same thing in different ways. There’s also applications, Vizenor says, “for anyone who has to process large volumes of documents and try to analyze them – legal, M&A, all are areas we target as apps for this.”