NASA’s Lessons Learned database is a vast, constantly updated collection knowledge and experience from past missions, which it relies on for planning future projects and expeditions into space.
With detailed information from every mission going back as far as the sixties, every record is reviewed and approved before inclusion. As well as NASA staff, thousands of scientists, engineers, educators and analysts access the database every month from private sector and government organizations.
As it has swollen in size, the interface used internally to query the dataset – a keyword-based search built on a PageRank-style algorithm – was becoming unwieldy. Chief Knowledge Architect David Meza spoke to me recently, and told me that the move to the graph-based, open source Neo4J management system has significantly cut down on time engineers and mission planners spend combing through keyword-based search results.
Meza says “This came to light when I had a young engineer come to me because he was trying to explore our Lessons Learned database – but sometimes it’s hard to find the information you want in that database.
“He had 23 key terms he was trying to search for across the database of nearly 10 million documents, and because it was based on a PageRank algorithm the records nearest the top of the results were there because they were most frequently accessed, not necessarily because they had the right information.”
The gist of the problem was that even after searching the database, the engineer was left with around 1,000 documents which would need to be read through individually to know if they held information he needed.
“I knew there had to be something better we could do,” Meza says. “I started looking at graph database technologies and came across Neo4J. What was really interesting was the way it made it easier to combine information and showcase it in a graph form.
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