Difference Operators in Simulation Data Warehouses
Jing Zhao†, Yoshiharu Ishikawa, Yukiko Wakita, and Kento Sugiura
Graduate School of Information Science, Nagoya University
Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan
In analyzing observation data and simulation results, there are frequent demands for comparing more than one data on the same subject to detect any differences between them. For example, comparison of observation data for an object in a certain spatial domain at different times or comparison of spatial simulation data with different parameters. Therefore, this paper proposes the difference operator in spatio-temporal data warehouses, which store temporal and spatial observation data and simulation data. The requirements for the difference operator are summarized, and the approaches to implement them are presented. In addition, the proposed approach is applied to the mass evacuation of simulation data in a tsunami disaster, and its effectiveness is verified. Extensions of the difference operator and their applications are also discussed.
-  S. Acharya, V. Poosala, and S. Ramaswamy, “Selectivity estimation in spatial databases,” In ACM SIGMOD, pp. 13–24, 1999.
-  N. Bruno, S. Chaudhuri, and L. Gravano “STHoles: A multidimensional workload-aware histogram,” In ACM SIGMOD, pp. 211–222, May, 2001.
-  H. Ehsan, M. A. Sharaf, and P. K. Chrysanthis, “MuVE: Efficient multi-objective view recommendation for visual data exploration,” In ICDE, pp. 731–742, 2016.
-  L. Gómez, B. Kuijpers, and B. Moelans, “A survey of spatio-temporal data warehousing,” International Journal of Data Warehousing and Mining, Vol.5, No.3, pp. 28–55, 2009.
-  Y. Ioannidis, “The history of histograms (abridged),” In VLDB, pp. 19–30, 2003.
-  Y. Ishikawa, “Research trend and future prospects for large-scale data analytics,” IEICE Trans. on Information and Systems (Japanese Edition), J97-D(4), pp. 718–728, 2014 (in Japanese).
-  L. Leonardi, G. Marketos, E. Frentzos, N. Giatrakos, S. Orlando, N. Pelekis, A. Raffaetà, A. Roncato, C. Silvestri, and Y. Theodoridis, “T-Warehouse: Visual OLAP analysis on trajectory data,” In Proc. ICDE, pp. 1141–1144, 2010.
-  H. Lustosa, F. Porto, P. Blanco, and P. Valduriez, “Database system support of simulation data,” PVLDB, Vol.9, No.13, pp. 1329–1340, Sept. 2016.
-  A. Parameswaran, N. Polyzotis, and H. Garcia-Molina, “SeeDB: Visualizing database queries efficiently,” Proceedings of the VLDB Endowment, Vol.7, No.4, pp. 325–328, 2013.
-  Paradigm4: Creators of SciDB a computational DBMS, http://www.paradigm4.com/ [accessed October 1, 2016]
-  M. Stonebraker, P. Brown, A. Poliakov, and S. Raman, “The architecture of SciDB,” In SSDBM, volume 6809 of LNCS, pp. 1–16, 2011.
-  M. Stonebraker, P. Brown, D. Zhang, and J. Becla, “SciDB: A database management system for applications with complex analytics,” IEEE Computational Science & Engineering, Vol.15, No.3, pp. 54–62, 2013.
-  A. Vaisman and E. Zimányi, “Data Warehouse Systems: Design and Implementation,” Springer, 2014.
-  J. Zhao, K. Sugiura, Y. Wang, and Y. Ishikawa, “Simulation data warehouse for integration and analysis of disaster information,” Journal of Disaster Research, Vol.11, No.2, pp. 255–264, 2016.
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