David Meza, chief knowledge architect at the National Aeronautics and Space Administration’s Johnson Space Center, is trying to find a way to share visual data so that a NASA employee at the Kennedy Space Center in Florida can log in to a computer and see what Meza and his team have been working on in their Texas-based studio.
This project to streamline visualization tools falls under a broader initiative to link the agency, especially in regard to big data. Recently, Meza and about 50 other NASA scientists have collaborated to create and execute strategy for a master data management plan, which was concocted in December. These collaborators meet twice a year at one of the 10 NASA space centers; their next big data plan meeting will occur in either September or October.
“We’re starting small,” Meza said. “We’re looking at ways of doing it smart. It’s a living thing. Data changes every day.”
NASA manages and stores more data than most other Federal agencies. The agency must confront and control the data collected from its many branches, missions, and projects.
In addition to working on ways to visualize data, Meza and his team use text analytics to improve query results. Meza said that another focus is honing communication between those who specialize in knowledge management, information architecture, and data science.
“Big data is many different things to many different people. My group has to understand all the different languages,” Meza said. “It’s important to learn how to not talk across each other, but with each other.”
The data strategy’s projects extend beyond linking visual images across space centers. Other aspects of the master plan involve a Data Fellows Program, in which selected candidates will work for NASA on agency-specific problems for terms of 6-12 months. Meza stated that NASA anticipates the first fleet of fellows to arrive in September. The strategy will also incorporate a Data Steward Program, in which NASA scientists who are experts in a certain field can advise branches on how to manage data properly.
“The important part is how we actually use big data,” Meza said. “It’s important that we are able to manage and analyze big data.”
