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An Approach to Navigating Data Cubes with a Hierarchical Visualization Technique

계층적 시각화 기법을 활용한 데이터 큐브의 탐색 방안

  • Oh, Mi-Hwa (Industrial & Information Systems Engineering, Soongsil Univ.) ;
  • Hwang, Man-Mo (Industrial & Information Systems Engineering, Soongsil Univ.) ;
  • Choi, Jung-Woo (Industrial & Information Systems Engineering, Soongsil Univ.) ;
  • Choi, In-Soo (Industrial & Information Systems Engineering, Soongsil Univ.)
  • 오미화 (숭실대학교 대학원 산업.정보시스템공학과) ;
  • 황만모 (숭실대학교 대학원 산업.정보시스템공학과) ;
  • 최정우 (숭실대학교 대학원 산업.정보시스템공학과) ;
  • 최인수 (숭실대학교 산업.정보시스템공학과)
  • Received : 2011.01.24
  • Accepted : 2011.01.31
  • Published : 2011.02.28

Abstract

To efficiently analyze complex and voluminous data, OLAP systems increasingly provide functionalities for visual exploration of the data allowing end-users to navigate the desired view of the data cube. This paper only deals with data cubes whose schemas represented like the exclusive symmetric hierarchy which is not addressed by current OLAP implementations. This paper presents a conceptual classification of abstraction hierarchies, and an approach to navigating data cubes with a hierarchical visualization technique. The hierarchical visualization technique is developed by using the transitive closure of a binary relation. The approach is exemplified using a real-world study from the domain of national license administration.

다량의 복잡한 데이터를 잘 분석하고자 하는 의도로 최종 사용자가 데이터 큐브 내에 있는 여러 데이터 뷰 중에서 바라는 데이터 뷰를 시각적으로 탐색하게끔 해주는 기능을 OLAP 시스템에서는 계속 마련하고 있다. 본 연구에서는 자신의 스키마가 현 OLAP 시스템에서는 구현될 수 없는 배타적 대칭 계층과 같은 것이 되는 그런 데이터 큐브 만 대상으로 하고자 한다. 본 연구에서는 추상 계층의 개념적 분류를 하였고, 본 연구에서 개발한 계층적 시각화기법을 활용하여 데이터 큐브를 탐색해 나가는 방안을 제시하고 있다. 계층적 시각화 기법은 이항 추이폐포 개념을 활용하여 개발하였다. 국가자격관리 영역을 예로 들어 이 방안을 설명하고 있다.

Keywords

References

  1. Surajit Chaudhuri, and Umeshwar Dayal, "An Overview of Data Warehousing and OLAP Technology," ACM SIGMOD Record, Vol. 26, No. 1, pp. 65-74, 1997. https://doi.org/10.1145/248603.248616
  2. DuckSung Lee, and InSoo Choi, "Design of an Inference Control Process in OLAP Data Cubes," Journal of The Korea Society of Computer and Information, Vol. 14, No. 5, pp. 183-193, May. 2009.
  3. DuckSung Lee, and InSoo Choi, "A Strategy for Inference Control of Official Statistics," Journal of The Korea Society of Computer and Information,, Vol. 14, No. 11, pp. 200-211, November. 2009.
  4. Alfredo Cuzzocrea, Domenico Sacca, and Paolo Serafino, "A Hierarchy-Driven Compression Technique for Advanced OLAP Visualization of Multidimensional Data Cubes," Proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery, LNCS 4081, pp. 106- 119, 2006.
  5. Svetlana Mansmann, and Marc H. Scholl, "Exploring OLAP Aggregates with Hierarchical Visualization Techniques," Proceedings of the 22nd Annual ACM Symposium on Applied Computing, Multimedia & Visualization Track, pp. 1067-1073, 2007.
  6. Alfredo Cuzzocrea, and Svetlana Mansmann, "Models, Issues, and Techniques in OLAP Visualization," IGI Golbal, pp. 1-8, 2009.
  7. John Miles Smith, and Diane C.P.Smith, "Database Abstractions: Aggregation and Generalization," ACM Transactions on Database Systems, Vol. 2, No. 2, pp. 105-133, June. 1977. https://doi.org/10.1145/320544.320546
  8. David M. Kroenke, "Database Processing," PEARSON, pp. 125-188, 2010.
  9. E. Malinowski, and E. Zimanyi, "OLAP Hierarchies: A Conceptual Perspective," LNCS 3084, pp. 477-49, 2004.
  10. John Miles Smith, and Diane C.P.Smith, "Database Abstractions: Aggregation," ACM Transactions on Database Systems, Vol. 2, No. 2, pp. 105-133, June. 1977. https://doi.org/10.1145/320544.320546
  11. Aggregation, http://krdic.naver.com
  12. EM018587, KRIVET, 2003.
  13. EM015527, KRIVET, 2002.
  14. EM015526, KRIVET, 2000.
  15. SeHyeon Jang, HanJu Yu, and InSoo Choi, "Design of a Hierarchical Dimension of the Bill of Materials Type," Journal of the Korea Society of Computer and Information, Vol. 11, No. 4, pp. 244-250, Sept. 2006.
  16. Carlos A. Hurtado, and Alberto O. Mendelzon. Jensen, "Reasoning about Summarizability in Heterogeneous Multidimensional Schemas", LNCS 1973, pp. 375-389, 2001.
  17. David M. Kroenke, "Database Processing," PEARSON, pp. 182, 2010.
  18. Svetlana Vinnik, and Florian Mansmann, "From Analysis to Interactive Exploration: Building Visual Hierarchies from OLAP Cubes,"LNCS 3896, pp.496-514, 2006.
  19. Svetlana Mansmann, and Marc H. Scholl, "Extending Visual OLAP for Handling Irregular Dimensional Hierarchies," LNCS 4081, pp. 95-105, 2006.
  20. H. J. Lenz, and A. Shoshani, "Summarizability in OLAP and statistical data bases," In Proceedings of 9th International Conference on Scientific and Statistical Database Management, pp. 132-43, 1997.
  21. Torben Bach Pedersen, Christian S. Jensen, and Curtis E. Dyreson, "A foundation for capturing and querying complex multidimensional data," Information Systems Vol. 26, pp. 383-423, 2001. https://doi.org/10.1016/S0306-4379(01)00023-0
  22. Torben Bach Pedersen, and Christian S. Jensen, "Multidimensional Data Modeling for Complex Data," A Time Center Technical Report, pp. 1-27, 1998.
  23. Andreas Bauer, Wolfgang Hummer, and Wolfgang Lehner, "An Alternative Relational OLAP Modeling Approach," LNCS 1874, pp. 189-198, 2000.
  24. Transitive closure, http://en.wikipedia.org
  25. Xiaoyang Yo, "Transitive Closure of Binary Relation", http://imps.mcmaster.ca
  26. Erik Thomsen, "OLAP Solutions," pp. 132-133, John Wiley & Sons, 2002.
  27. Garrett M. Fitzmaurice, Nan M. Laird, and James H. Ware, "Applied Longitudinal Analysis," John Wiley & Sons, pp. 1-4, 2004.