Paper "Compressing Provenance Graphs" Accepted to CIKM Conference

July 17, 2012

The paper "Compressing Provenance Graphs" from Yulai Xie (HUST), Kiran-Kumar Muniswamy-Reddy (Harvard University), Dan Feng (HUST), Yan Li (SSRC), Darrell D. E. Long (SSRC), Zhipeng Tan (HUST), and Lei Chen (HUST) has been accepted as a short paper for inclusion in the proceedings of The 21st ACM Conference on Information and Knowledge Management (CIKM) and for poster presentation at the conference.

Provenance is the metadata that describes the history of data objects. Provenance enables new functionality in a wide range of areas, including experimental documentation, security, search, and debugging. A number of systems have been built to capture provenance. Most of these systems focused on provenance collection, but the efficient long term storage of provenance has been largely ignored.

This paper analyzes the provenance collected from multiple workloads with a view towards efficient storage and proposes a hybrid scheme that takes advantage of the graph structure of provenance data and the inherent duplication in provenance data.

CRSS Contact: Li, Yan

Last modified 24 May 2019