Graphs are, by nature, 'unifying abstractions' that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?
We are witnessing an unprecedented growth of interconnected data, which underscores the vital role of graph processing in our society. Instead of a single, exemplary ("killer") application, we see big graph processing systems underpinning many emerging but already complex and diverse data management ecosystems, in many areas of societal interest.a