Managing Social Security Data in the Web 2.0 Era
Affiliation(s)
College of Literature, Law & Economics, Wuhan University of Science and Technology, Wuhan, China. School of Political Science & Public Administration, Wuhan University, Wuhan, China. State Key Lab of Software Engineering, Wuhan University, Wuhan, China.
College of Literature, Law & Economics, Wuhan University of Science and Technology, Wuhan, China. School of Political Science & Public Administration, Wuhan University, Wuhan, China. State Key Lab of Software Engineering, Wuhan University, Wuhan, China.
ABSTRACT
Social security data management is an important topic both in application of information management and in social security management. In the Web 2.0 era, more and more human information and healthcare information is released to the Internet through various approaches. This abundance makes managing social security data go beyond managing conventional social security database records. How to organize the conventional records together with the related information gathered from the Web is an interesting problem to solve to provide more convenient and powerful social security information service. In this paper, we introduce our initial work on building a Web-oriented social security information system named i-SSIS. I-SSIS is a database system which adopts a new object-role data model named INM model and deploys INM database system as its core. With the assistance of auxiliary tools to carry out social security information extraction, analyzing and query, i-SSIS can properly provide social security-related information gathered from the Web. We introduce the basic ideas of designing i-SSIS and describe the architecture and major components of the system.
Social security data management is an important topic both in application of information management and in social security management. In the Web 2.0 era, more and more human information and healthcare information is released to the Internet through various approaches. This abundance makes managing social security data go beyond managing conventional social security database records. How to organize the conventional records together with the related information gathered from the Web is an interesting problem to solve to provide more convenient and powerful social security information service. In this paper, we introduce our initial work on building a Web-oriented social security information system named i-SSIS. I-SSIS is a database system which adopts a new object-role data model named INM model and deploys INM database system as its core. With the assistance of auxiliary tools to carry out social security information extraction, analyzing and query, i-SSIS can properly provide social security-related information gathered from the Web. We introduce the basic ideas of designing i-SSIS and describe the architecture and major components of the system.
Cite this paper
L. Luo, H. Yang and X. Li, "Managing Social Security Data in the Web 2.0 Era," iBusiness, Vol. 4 No. 3, 2012, pp. 222-227. doi: 10.4236/ib.2012.43028.
L. Luo, H. Yang and X. Li, "Managing Social Security Data in the Web 2.0 Era," iBusiness, Vol. 4 No. 3, 2012, pp. 222-227. doi: 10.4236/ib.2012.43028.
References
[1] Department of Health of the United States, “Second Review of a New Data Management System for the Social Security Administration,” National Academies Publication, Washington DC, 1979. [2] P. A. Diamond, “A Framework for Social Security Analysis,” Journal of Public Economics, Vol. 8, No. 3, 1977, pp. 275-298. HUdoi:10.1016/0047-2727(77)90002-0U [3] S. Wu, Y. Zhao, H. Zhang, C. Zhang and L. Cao, “Debt Detection in Social Security by Adaptive Sequence Classification,” Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management, Vienna, 25-27 November 2009, pp. 192-203. [4] H. Zhang, Y. Zhao, L. Cao, C. Zhang and H. Bohlscheid, “Customer Activity Sequence Classification for Debt Prevention in Social Security”, Journal of Computer Science and Technology, Vol. 24, No. 6, 2009, pp. 1000-1009. HUdoi:10.1007/s11390-009-9288-2U [5] P. Lucas, “Bayesian Analysis, Pattern Analysis, and Data Mining in Health Care,” Current Opinion in Critical Care, Vol. 10, No. 5, 2004, pp. 399-403. HUdoi:10.1097/01.ccx.0000141546.74590.d6U [6] L. O. Gostin, J. T. Brezina, M. Powers, R. Kozloff, R. Faden and D. D. Steinauer, “Privacy and Security of Personal Information in a New Health Care System,” The Journal of American Medical Association, Vol. 270, No. 20, 1993, pp. 2487-2493. HUdoi:10.1001/jama.1993.03510200093038U [7] J. A. Lyman, K. Scully and J. H. Harrison, “The Development of Health Care Data Warehouses to Support Data Mining,” Clinics in Laboratory Medicine, Vol. 28, No. 1, 2008, pp. 55-71. HUdoi.org/10.1016/j.cll.2007.10.003U [8] S. M. Heathfield, “Human Resources Information System (HRIS)-HRIS Definition,” Technical Report, 2011 http://www.about.com [9] M. Liu and J. Hu, “Information Networking Model,” Proceedings of 28th International Conference on Conceptual Modeling (ER 2009), Gramado, 9-12 November 2009, pp. 131-144. [10] J. Hu, Q. Fu and M. Liu, “Query Processing in INM Database System,” Proceedings of 11th International Conference on Web Age Information Management (WAIM 2010), Chengdu, 15-17 July 2010 pp. 525-536 [11] J. Hu and M. Liu, “Modeling Context-Dependent Information”, Proceedings of 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, 2-6 November 2009, pp. 1669-1672. [12] L. Luo, H. Yang and X. Li, “Towards Human Resource Information Query on Temporal XML”, Proceedings of 3rd International Conference on Internet Technology and Applications (ITAP 2012), Wuhan, 18-20 August 2012. [13] The Pluto Searching Engine. http://pluto.whu.edu.cn
[1] Department of Health of the United States, “Second Review of a New Data Management System for the Social Security Administration,” National Academies Publication, Washington DC, 1979. [2] P. A. Diamond, “A Framework for Social Security Analysis,” Journal of Public Economics, Vol. 8, No. 3, 1977, pp. 275-298. HUdoi:10.1016/0047-2727(77)90002-0U [3] S. Wu, Y. Zhao, H. Zhang, C. Zhang and L. Cao, “Debt Detection in Social Security by Adaptive Sequence Classification,” Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management, Vienna, 25-27 November 2009, pp. 192-203. [4] H. Zhang, Y. Zhao, L. Cao, C. Zhang and H. Bohlscheid, “Customer Activity Sequence Classification for Debt Prevention in Social Security”, Journal of Computer Science and Technology, Vol. 24, No. 6, 2009, pp. 1000-1009. HUdoi:10.1007/s11390-009-9288-2U [5] P. Lucas, “Bayesian Analysis, Pattern Analysis, and Data Mining in Health Care,” Current Opinion in Critical Care, Vol. 10, No. 5, 2004, pp. 399-403. HUdoi:10.1097/01.ccx.0000141546.74590.d6U [6] L. O. Gostin, J. T. Brezina, M. Powers, R. Kozloff, R. Faden and D. D. Steinauer, “Privacy and Security of Personal Information in a New Health Care System,” The Journal of American Medical Association, Vol. 270, No. 20, 1993, pp. 2487-2493. HUdoi:10.1001/jama.1993.03510200093038U [7] J. A. Lyman, K. Scully and J. H. Harrison, “The Development of Health Care Data Warehouses to Support Data Mining,” Clinics in Laboratory Medicine, Vol. 28, No. 1, 2008, pp. 55-71. HUdoi.org/10.1016/j.cll.2007.10.003U [8] S. M. Heathfield, “Human Resources Information System (HRIS)-HRIS Definition,” Technical Report, 2011 http://www.about.com [9] M. Liu and J. Hu, “Information Networking Model,” Proceedings of 28th International Conference on Conceptual Modeling (ER 2009), Gramado, 9-12 November 2009, pp. 131-144. [10] J. Hu, Q. Fu and M. Liu, “Query Processing in INM Database System,” Proceedings of 11th International Conference on Web Age Information Management (WAIM 2010), Chengdu, 15-17 July 2010 pp. 525-536 [11] J. Hu and M. Liu, “Modeling Context-Dependent Information”, Proceedings of 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, 2-6 November 2009, pp. 1669-1672. [12] L. Luo, H. Yang and X. Li, “Towards Human Resource Information Query on Temporal XML”, Proceedings of 3rd International Conference on Internet Technology and Applications (ITAP 2012), Wuhan, 18-20 August 2012. [13] The Pluto Searching Engine. http://pluto.whu.edu.cn