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Position paper

Authors :
Hassan H. Halawa
Matei Ripeanu
Source :
GRADES-NDA@SIGMOD
Publication Year :
2021
Publisher :
ACM, 2021.

Abstract

Most of today's graph analytics systems model static graphs and do not support business use cases that require the ability to: (i) query the dynamic graph data for a time-evolving system, (ii) carry out investigations on its historical evolution, and (iii) audit past business decisions made with potentially stale or incorrect data. This position paper presents our vision for bi-temporal dynamic graph analytics, and sketches a design for a system that efficiently supports these requirements.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)
Accession number :
edsair.doi...........428dc608a6d827dcbd56c293d1b87c63