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姓名 劉宛舒(Wan-Shu Liu)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 以全面品質管理與資訊科技之角度探討氣象觀測系統的資料品質檢核
(A Study of Data Quality Examination for Meteorological Observation System: A Total Quality Management and IT Perspective)
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摘要(中) 在現今資訊化的時代下,資料品質之良窳對於企業營運具有重大且關鍵的影響。在氣象領域中,氣象資料的品質所扮演的角色亦是如此。然而,現有氣象品質控制之常見方式,主要著重於錯誤偵測與遺漏值偵測,即僅針對資料產出的結果做考慮,卻忽略了在作業流程上可能也會引發品質問題。因此,本研究旨在以全面品質管理(Total Quality Management,簡為TQM)之角度,特別是針對資料倉儲的系統性質以及流程專注的訴求之下,提出一全面性的氣象資料品質綜效架構(Total Meteorological Data Quality framework,簡為TMDQ)。同時,透過這一架構所建立的四個品質向度指標,協助氣象觀測人員能從不同面向來掌握氣象資料的各種品質。在實務應用上,本研究依據所提出的架構,實作出一個應用程式以幫助氣象觀測人員能適時且有效的提昇與維護氣象資料之品質。並且,為了驗證本研究提出的架構與所實作出之系統的可行性,本研究亦將TMDQ應用於中央氣象局的淡水觀測站之中,來展示系統功能與使用情形。最後,針對現有的運用與研究限制進行討論,並提出未來研究的可能方向。
摘要(英) In this information era, the quality of data is significant to enterprises. In meteorology, the quality of meteorological data also plays an important role in decision-making. However, the existing methods of meteorological data quality control focus on error detection and missing values detection, which aim at taking the output of dataset into account; whereas they neglect the quality problems arises from the processes. Therefore, this research aims to propose a comprehensive framework of the quality of meteorological data, termed Total Meteorological Data Quality framework (TMDQ). This framework is based on Total Quality Management (TQM), especially focusing on the demand of the system characteristics of data warehouse and the processes-focusing. Simultaneously, by the four quality indicators built by this framework, TMDQ can help observers from different views to handle a variety of meteorological data qualities. In the practical application, according to the proposed framework, this research implements an application to help observers to increase and maintain the quality of meteorological data. Moreover, to verify the feasibility of the proposed framework and the implemented system, this research applies TMDQ to the Danshui observing station of Central Weather Bureau to demonstrate the proposed system and the test situation. Finally, discussion and suggestions are presented for the existing application and we propose the probable direction of the future work.
關鍵字(中) ★ 資料品質
★ 氣象觀測系統
★ 氣象資料
★ 全面品質管理
★ 資料倉儲
關鍵字(英) ★ Data warehouse
★ Total quality management
★ Meteorological data
★ Weather observing system
★ Data quality
論文目次 摘要  i
Abstract  ii
誌謝  iii
目錄  iv
圖目錄  vi
表目錄  viii
第一章 緒論  1
 1-1 研究背景  1
 1-2 研究動機與問題  2
 1-3 研究目的與預期效益  2
 1-4 論文架構  3
第二章 文獻探討  4
 2-1 資料倉儲  5
  2-1-1 資料倉儲的定義  5
  2-1-2 資料倉儲的架構  6
  2-1-3 資料倉儲的運用與相關議題  7
 2-2 資料品質與全面品質管理  8
  2-2-1 資料品質與全面品質管理的定義  8
  2-2-2 資料品質的衡量方式  9
 2-3 氣象領域之現有品質管理方式  12
  2-3-1 品質問題分類  12
  2-3-2 資料品質控制-極端值判定程序  12
  2-3-3 評論  15
第三章 研究設計與方法  16
 3-1 研究架構  16
 3-2 架構之細部說明  18
  3-2-1 準確性  18
  3-2-2 完整性  18
  3-2-3 一致性  19
  3-2-4 即時性  20
 3-3 流程與功能架構  20
第四章 系統實作與展示  28
 4-1 中央氣象局背景介紹  28
 4-2 系統實作與說明  29
  4-2-1 初步設定  32
  4-2-2 系統執行  35
第五章 分析與討論  44
 5-1 信賴度評估  44
 5-2 效益預測  45
 5-3 研究限制  49
第六章 結論與展望  50
 6-1 研究結論與貢獻  50
 6-2 未來方向  50
參考文獻  52
參考文獻 中文部分
邱清安、林博雄與謝旻耕 (2005)。台灣地區氣象測站之詮釋資料與日氣溫、日降水之資料檢定。氣象學報,45(3),33-45。
張玲星與顏河清 (2006)。電腦化過程參與成員認知差異之研究-以科技框架分析。資訊管理展望,8(1),27-44。
葉美春 (2006)。使用者對知識管理系統接受度影響因素初探-以中華電信為例。2006電子商務與數位生活研討會。
英文部分
Ahmad, I., Azhar, S., & Lukauskis, P. (2004). Development of a decision support system using data warehousing to assist builders/developers in site selection. Automation in Construction, 13(4), 525-542.
Alexandersson, H., & Moberg, A. (1997). Homogenization of Swedish temperaturedata. Part:Homogeneity test for linear trends. International Journal of Climatology, 17(1), 25-34.
Ballou, D. P., & Pazer, H. L. (1985). Modeling data and process quality in multi-input, multi-output information systems. Management Science, 31(2), 150-162.
Bounds, G., Yorks, L., Adams, M., & Ranney, G. (1994). Beyond total quality management: Toward the emerging paradigm. New York: McGraw-Hill.
Chau, K. W., Cao, Y., Anson, M., & Zhang, J. (2003). Application of data warehouse and decision support system in construction management. Automation in Construction, 12(2), 213-224.
Chaudhuri, S., & Dayal, U. (1997). An overview of data warehousing and OLAP technology. SIGMOD Rec., 26(1), 65-74.
Chen, C. Y., Chi, Y. L., & Wolfe, P. (2005). An object-oriented quality framework and optimization models for comprehensively understanding and managing data quality in data warehouse application. International Journal of Operations Research, 2(2), 1-8.
Chen, C. Y., Kuo, C. Y., & Chen, P. C. (2007). A preliminary study of data quality measure with the emphasis on error criticality. Paper presented at the 2007 Industrial Engineering Research Conference (IERC).
Cohen, S., & Brand, R. (1993). Total quality management in government. San Francisco, CA: Jossey-Bass Publishers.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Dehartdt, R. B. (1991). Public administration. Belmost, CA: Wadsworth.
Durre, I., Menne, M. J., Gleason, B. E., Houston, T. G., & Vose, R. S. (2010). Comprehensive automated quality assurance of daily surface observations. Journal of Applied Meteorology and Climatology, 49(8), 1615-1633.
Easterling, D. R., & Peterson, T. C. (1995). A new method for detecting undocumented discontinuities in climatological time series. International Journal of Climatology, 15(4), 369-377.
Einfalt , T., & Michaelides, S. (2008). Quality control of precipitation data. Precipitation: Advances in measurement, estimation and prediction. (pp. 101-126). Berlin: Springer.
English, L. (1999). Improving data warehouse and business information quality. New York: John Wiley and Sons, Inc.
Feng, S., Hu, Q., & Qian, W. (2004). Quality control of daily meteorological data in China, 1951–2000: A new dataset. International Journal of Climatology, 24(7), 853-870.
Fiebrich, C. A., Morgan, C. R., McCombs, A. G., Hall, P. K., & McPherson, R. A. (2010). Quality assurance procedures for mesoscale meteorological data. Journal of Atmospheric and Oceanic Technology, 27(10), 1565-1582.
Fotopoulos, C. B., & Psomas, E. L. (2009). The impact of “soft” and “hard” TQM elements on quality management results. International Journal of Quality & Reliability Management, 26(2), 150-163.
Gonzalez-Rouco, J. F., Jimenez, J. L., Quesada, V., & Valero, F. (2001). Quality control and homogeneity of precipitation data in the southwest of Europe. Journal of Climate, 14(5), 964-978.
Graybeal, D. Y., DeGaetano, A. T., & Eggleston, K. L. (2004). Complex quality assurance of historical hourly surface airways meteorological data. Journal of Atmospheric and Oceanic Technology, 21(8), 1156-1169.
Hoang, D. T., Igel, B., & Laosirihongthong, T. (2006). The impact of total quality management on innovation: Findings from a developing country. International Journal of Quality & Reliability Management, 23(9), 1092-1117.
Hoven, J. v. d. (1998). Data warehousing: Bringing it all together. Information Systems Management, 15(2), 1 - 5.
Huang, J., Yuan, M., Liu, X., & Shang, X. (2010). The design and implementation of MDSS based on data warehouse. Paper presented at the 2010 International Conference on Computing, Control and Industrial Engineering (CCIE).
Inmon, W. H. (1990). Building the data warehouse. Boston: QED Information Sciences, Inc.
Jang, Y., Ishii, A. T., & Wang, R. Y. (1995). A qualitative approach to automatic data quality judgment. J. Organ. Comput., 5(2), 101-121.
Janson, M. A. (1988). Data quality: The Achilles heel of end-user computing. Omega, 16(5), 491-502.
Jeffrey, S. J., Carter, J. O., Moodie, K. B., & Beswick, A. R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environmental Modelling & Software, 16(4), 309-330.
Jukic, N., & Nestorov, S. (2006). Comprehensive data warehouse exploration with qualified association-rule mining. Decision Support Systems, 42(2), 859-878.
Kesh, S. (1995). Evaluating the quality of entity relationship models. Information and Software Technology, 37(12), 681-689.
Kimball, R., Reeves, L., Ross, M., & Thornthwaite, W. (1998). The data warehouse lifecycle toolkit: Expert methods for designing, developing, and deploying data warehouses. New York: John Wiley & Sons, Inc.
Klein Tank, A. M. G., Wijngaard, J. B., Konnen, G. P., Bohm, R., Demaree, G., Gocheva, A., et al. (2002). Daily dataset of 20th-century surface air temperature and precipitation series for the European climate assessment. International Journal of Climatology, 22(12), 1441-1453.
Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: A methodology for information quality assessment. Information & Management, 40(2), 133-146.
Madnick, S. E., Wang, R. Y., Lee, Y. W., & Zhu, H. (2009). Overview and framework for data and information quality research. J. Data and Information Quality, 1(1), 1-22.
Manton, M., Della-Marta, P., Haylock, M., Hennessy, K., Nicholls, N., Chambers, L., et al. (2001). Trends in extreme daily rainfall and temperature in Southeast Asia and the South Pacific: 1961–1998. International Journal of Climatology, 21(3), 269-284.
March, S. T., & Hevner, A. R. (2007). Integrated decision support systems: A data warehousing perspective. Decision Support Systems, 43(3), 1031-1043.
Meek, D. W., & Hatfield, J. L. (1994). Data quality checking for single station meteorological databases. Agricultural and Forest Meteorology, 69(1-2), 85-109.
Morris, M. G., & Dillon, A. (1997). How user perceptions influence software use. IEEE Softw., 14(4), 58-65.
Musa, M., Gruter, E., Abb, t. M., Haberli, C., Haller, E., Kung, U., et al. (2003). Quality control tools for meteorological data in the Meteoswiss data warehouse system. Paper presented at the ICAM/MAP 2003.
Orr, K. (1998). Data quality and systems theory. Commun. ACM, 41(2), 66-71.
Peck, E. L. (1997). Quality of hydrometeorological data in cold regions. Journal of the American Water Resources Association., 33(1), 125-134.
Peterson, T. C., Easterling, D. R., Karl, T. R., Groisman, P., Nicholls, N., Plummer, N., et al. (1998). Homogeneity adjustments of in situ atmospheric climate data: A review. International Journal of Climatology, 18(13), 1493-1517.
Ponniah, P. (2001). Data warehousing fundamentals. New York: Wiley-Interscience.
Raghunathan, S. (1999). Impact of information quality and decision-maker quality on decision quality: A theoretical model and simulation analysis. Decision Support Systems, 26(4), 275-286.
Redman, T. C. (1997). Data quality for the information age. Boston: Artech House, Inc.
Reek, T., Doty, S. R., & Owen, T. W. (1992). A deterministic approach to the validation of historical daily temperature and precipitation data from the cooperative network. Bulletin of the American Meteorological Society, 73(6), 753-762.
Sargent, P. (1992). Data quality in materials information systems. Computer-Aided Design, 24(9), 477-490.
Sila, I., & Ebrahimpour, M. (2005). Critical linkages among TQM factors and business results. International Journal of Operations & Production Management, 25(11), 1123-1155.
Strong, D. M. (1997). IT process designs for improving information quality and reducing exception handling: A simulation experiment. Information & Management, 31(5), 251-263.
Tari, J. J. (2005). Components of successful total quality management. The TQM Magazine, 17(2), 182-194.
Tayi, G. K., & Ballou, D. P. (1998). Examining data quality. Commun. ACM, 41(2), 54-57.
Vassiliadis, P., Quix, C., Vassiliou, Y., & Jarke, M. (2001). Data warehouse process management. Information Systems, 26(3), 205-236.
Vincent, L. A., Zhang, X., Bonsal, B. R., & Hogg, W. D. (2002). Homogenization of daily temperatures over Canada. Journal of Climate, 15(11), 1322-1334.
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. J. Manage. Inf. Syst., 12(4), 5-33.
Watson, H. J., Annino, D. A., Wixom, B. H., Avery, K. L., & Rutherford, M. (2001). Current practices in data warehousing. Information Systems Management, 18(1), 47-55.
Zahumensky, L. (2004). Guidelines on quality control procedures for data from automatic weather stations. CBS/OPAG-IOS/ET, 25.
指導教授 陳仲儼(Chung-Yang Chen) 審核日期 2011-7-20
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