The National Aeronautics and Space Administration (NASA) is looking to adopt automated data analysis as it moves forward in its technology modernization efforts, a top NASA official said on Tuesday at the Red Hat Government Symposium powered by MeriTalk.
Josiah Johnson, systems architect for the Operations Support Center at NASA, said that the agency’s Marshall Space Flight Center – located in Huntsville, Ala. – is working to use artificial intelligence (AI) improve the efficiency and scalability of data analysis and output to entities relying on that data.
AI and automated processes can help expedite processes to get software updates or new technology off the ground and into space, Johnson said.
“One of the things that we, specifically at Marshall, are doing is completely making it to where any customer can come in and get there as fast as possible,” said Johnson.
“[We] are preparing and putting the groundwork to make it to where any customer that wants to do that type of environment, any engagement …can come in, plug in and have a fast connection, as well as a suite of applications that can do intelligent pieces with our data that’s coming down, and applying those types of AI models to every different piece,” he said.
Data analysis automation will also complement the work of NASA staff who currently work at all hours of the day, all week-long, to process data, Johson explained.
By implementing “intelligent infrastructure” and leveraging “self-aware” technologies, NASA aims to streamline workflows that currently require multiple teams to review data, thus boosting scientific output without expanding operational resources.
“Maybe we could streamline how much science one individual person can look at in one time,” said Johnson. “Not that we’re trying to reduce or move footprints and things like that – but make it more efficient so we can do more science.”
Johnson also highlighted the importance of being “data aware” as NASA continues to modernize its operations, noting that in an era of data proliferation, the careful management of information and strategic decision making about where and how data is processed is key. “It’s just understanding what you’re doing with your data end-to-end, and what you want to do with it,” he said.
