The Future is Big Graphs! A Community View on Graph Processing Systems

Abstract

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?

12 pages, 3 figures, collaboration between the large-scale systems and data management communities, work started at the Dagstuhl Seminar 19491 on Big Graph Processing Systems, to be published in the Communications of the ACM

References in corpus (3)

• Graph Summarization Methods and Applications: A Survey
• High-Level Programming Abstractions for Distributed Graph Processing
• G-CORE: A Core for Future Graph Query Languages

Cited by in corpus (11)

• Construction of Knowledge Graphs: State and Challenges
• PG-Schema: Schemas for Property Graphs
• Graph-guided random forest for gene set selection
• PolarFly: A Cost-Effective and Flexible Low-Diameter Topology
• PG-Triggers: Triggers for Property Graphs
• Common Foundations for SHACL, ShEx, and PG-Schema
• Conjunctive Regular Path Queries under Injective Semantics
• MINE GRAPH RULE: A New Cypher-like Operator for Mining Association Rules on Property Graphs
• Hyperownership: Beyond the Current State of Interaction with Digital Property
• Pebbles, Graphs, and a Pinch of Combinatorics: Towards Tight I/O Lower Bounds for Statically Analyzable Programs
• A Rule-based Operational Semantics of Graph Query Languages