Simulation Data Summarization Based on Spatial Histograms

Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

Abstract:

In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: Simulation data, data summarization, spatial histograms, exploration and visualization.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.2363254

References:

[1] S. Acharya, V. Poosala, and S. Ramaswamy. Selectivity estimation in spatial databases. In SIGMOD, pages 13–24, 1999.
[2] L. Battle, M. Stonebraker, and R. Chang. Dynamic reduction of query result sets for interactive visualizaton. 2013 IEEE International Conference on Big Data, pages 1–8, 2013.
[3] N. Bruno, S. Chaudhuri, and L. Gravano. STHoles: A multidimensional workload-aware histogram. In SIGMOD, pages 211–222, May 2001.
[4] H. Ehsan, M. A. Sharaf, and P. K. Chrysanthis. MuVE: Efficient multi-objective view recommendation for visual data exploration. In ICDE, pages 731–742, 2016.
[5] A. Eldawy and M. F. Mokbel. The era of big spatial data: A survey. Found. Trends databases, 6(3-4):163–273, Dec. 2016.
[6] V. Hristidis, S. C. Chen, T. Li, S. Luis, and Y. Deng. Survey of data management and analysis in disaster situations. J. Syst. Softw., 83(10):1701–1714, Oct. 2010.
[7] Y. Ioannidis. The history of histograms (abridged). In VLDB, pages 19–30, 2003.
[8] H. V. Jagadish, N. Koudas, S. Muthukrishnan, V. Poosala, K. C. Sevcik, and T. Suel. Optimal histograms with quality guarantees. In VLDB, pages 275–286, 1998.
[9] S. Muthukrishnan, V. Poosala, and T. Suel. On rectangular partitionings in two dimensions: Algorithms, complexity, and applications. In ICDT, pages 236–256, 1999.
[10] A. Parameswaran, N. Polyzotis, and H. Garcia-Molina. SeeDB: Visualizing database queries efficiently. Proceedings of the VLDB Endowment, 7(4):325–328, 2013.
[11] V. Poosala and Y. E. Ioannidis. Selectivity estimation without the attribute value independence assumption. In VLDB, pages 486–495, 1997.
[12] X. Song, Q. Zhang, Y. Sekimoto, R. Shibasaki, N. J. Yuan, and X. Xie. A simulator of human emergency mobility following disasters: Knowledge transfer from big disaster data. In AAAI, pages 730–736, 2015.