The Future is Big Graphs! A Community View on Graph Processing Systems
Sherif Sakr
A. Bonifati
H. Voigt
Alexandru Iosup
Khaled Ammar
Renzo Angles
Walid Aref
Marcelo Arenas
Maciej Besta
P. Boncz
Khuzaima S. Daudjee
Emanuele Della Valle
Stefania Dumbrava
O. Hartig
Bernhard Haslhofer
T. Hegeman
J. Hidders
Katja Hose
Adriana Iamnitchi
Vasiliki Kalavri
Hugo Kapp
W. Martens
M. Tamer Ozsu
E. Peukert
Stefan Plantikow
Mohamed Ragab
M. Ripeanu
S. Salihoglu
Christian Schulz
P. Selmer
Juan Sequeda
Joshua Shinavier
Gábor Szárnyas
Riccardo Tommasini
Antonino Tumeo
Alexandru Uta
A. Varbanescu
Hsiang-Yun Wu
N. Yakovets
Da Yan
Eiko Yoneki
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?
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