To extract the needles of useful information out of haystacks of data, data scientists need increasingly powerful methods of machine learning. “In almost every practical application involving graphs, there exist nongraph data of great relevance. Examples of non-graph information include a person’s age and residence ZIP code, which are individual attributes. “In almost every practical application involving graphs, there exist nongraph data of great relevance,” Nosratinia said. The second component of Nosratinia’s research addresses data security.