ACM Home Page
Please provide us with feedback. Feedback
Methodologies for data quality assessment and improvement
Full text PdfPdf (1.68 MB)
Source
ACM Computing Surveys (CSUR) archive
Volume 41 ,  Issue 3  (July 2009) table of contents
Article No. 16  
Year of Publication: 2009
ISSN:0360-0300
Authors
Carlo Batini  Università di Milano - Bicocca, Milano, Italy
Cinzia Cappiello  Politecnico di Milano
Chiara Francalanci  Politecnico di Milano
Andrea Maurino  Università di Milano - Bicocca, Milano, Italy
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 416,   Downloads (12 Months): 1092,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1541880.1541883
What is a DOI?

ABSTRACT

The literature provides a wide range of techniques to assess and improve the quality of data. Due to the diversity and complexity of these techniques, research has recently focused on defining methodologies that help the selection, customization, and application of data quality assessment and improvement techniques. The goal of this article is to provide a systematic and comparative description of such methodologies. Methodologies are compared along several dimensions, including the methodological phases and steps, the strategies and techniques, the data quality dimensions, the types of data, and, finally, the types of information systems addressed by each methodology. The article concludes with a summary description of each methodology.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Aiken, P. 1996. Data Reverse Engineering. McGraw Hill.
3
 
4
 
5
 
6
Ballou, D. and Pazer, H. 1985. Modeling data and process quality in multi-input, multi-output information systems. Manag. Sci. 31, 2.
 
7
 
8
Basile, A., Batini, C., Grega, S., Mastrella, M., and Maurino, A. 2007. Orme: A new methodology for information quality and basel II operational risk. In Proceeedings of the 12th International Conference of Information Quality, Industrial Track.
 
9
Basili, V., Caldiera, C., Rombach, H. 1994. Goal question metric paradigm.
 
10
Baskarada, S., Koronios, A., and Gao, J. 2006. Towards a capability maturity model for information quality management: a tdqm approach. In Proceedings of the 11th International Conference on Information Quality.
 
11
 
12
 
13
Bertolazzi, P., Santis, L. D., and Scannapieco, M. 2003. Automatic record matching in cooperative information systems. In Proceedings of the ICDT International Workshop on Data Quality in Cooperative Information Systems (DQCIS).
 
14
Bettschen, P. 2005. Master data management (MDM) enables IQ at Tetra Pak. In Proceedings of the 10th International Conference on Information Quality.
 
15
 
16
Bovee, M., Srivastava, R., and Mak, B. September 2001. A conceptual framework and belief-function approach to assessing overall information quality. In Proceedings of the 6th International Conference on Information Quality.
17
 
18
 
19
Calvanese, D., De Giacomo, D., and Lenzerini, M. 1999. Modeling and querying semi-structured data. Network. Inform. Syst. J. 2, 2, 253--273.
 
20
Cappiello, C., Francalanci, C., and Pernici, B. 2003. Preserving Web sites: A data quality approach. In Proceedings of the 7th International Conference on Information Quality (ICIQ).
 
21
Cappiello, C., Francalanci, C., Pernici, B., Plebani, P., and Scannapieco, M. 2003b. Data quality assurance in cooperative information systems: a multi-dimension certificate. In Proceedings of the ICDT International Workshop on Data Quality in Cooperative Information Systems (DQCIS).
 
22
Catarci, T., and Scannapieco, M. 2002. Data quality under the computer science perspective. Archivi Computer 2.
 
23
Chapman, A., Richards, H., and Hawken, S. 2006. Data and information quality at the Canadian institute for health information. In Proceedings of the 11th International Conference on Information Quality.
 
24
 
25
Corey, D., Cobler, L., Haynes, K., and Walker, R. 1996. Data quality assurance activities in the military health services system. In Proceedings of the 1st International Conference on Information Quality. 127--153.
 
26
 
27
Data Warehousing Institute. 2006. Data quality and the bottom line: Achieving business success through a commitment to high quality data. http://www.dw-institute.com/.
 
28
De Amicis, F., Barone, D., and Batini, C. 2006. An analytical framework to analyze dependencies among data quality dimensions. In Proceedings of the 11th International Conference on Information Quality (ICIQ). 369--383.
 
29
De Amicis, F. and Batini, C. 2004. A methodology for data quality assessment on financial data. Studies Commun. Sci. SCKM.
 
30
De Michelis, G., Dubois, E., Jarke, M., Matthes, F., Mylopoulos, J., Papazoglou, M., Pohl, K., Schmidt, J., Woo, C., and Yu, E. 1997. Cooperative Information Systems: A Manifesto. In Cooperative Information Systems: Trends & Directions, M. Papazoglou and G. Schlageter, Eds. Academic-Press.
 
31
De Santis, L., Scannapieco, M., and Catarci, T. 2003. Trusting data quality in cooperative information systems. In Proceedings of the 11th International Conference on Cooperative Information Systems (CoopIS). Catania, Italy.
 
32
Dedeke, A. 2005. Building quality into the information supply chain. Advances in Management Information Systems-Information Quality Monograph (AMIS-IQ) Monograph. R. Wang, E. Pierce, S. Madnick, and Fisher C.W., Eds.
 
33
DQI. 2004. Data quality initiative framework. Project report. www.wales.nhs.uk/sites/documents/319/DQI_Framwork_Update_Letter_160604.pdf
 
34
 
35
English, L. 2002. Process management and information quality: how improving information production processes improved information (product) quality. In Proceedings of the 7th International Conference on Information Quality (ICIQ). 206--211.
 
36
Eppler, M. and Helfert, M. 2004. A classification and analysis of data quality costs. In Proceedings of the 9th International Conference on Information Systems (ICIQ).
 
37
Eppler, M. and Münzenmaier, P. 2002. Measuring information quality in the Web context: A survey of state-of-the-art instruments and an application methodology. In Proceedings of the 7th International Conference on Information Systems (ICIQ).
 
38
Falorsi, P., Pallara, S., Pavone, A., Alessandroni, A., Massella, E., and Scannapieco, M. 2003. Improving the quality of toponymic data in the italian public administration. In Proceedings of the ICDT Workshop on Data Quality in Cooperative Information Systems (DQCIS).
 
39
Fellegi, I. P., and Holt, D. 1976. A systematic approach to automatic edit and imputation. J. Amer. Stat. Assoc. 71, 353, 17--35.
 
40
 
41
Fraternali, P., Lanzi, P., Matera, M., and Maurino, A. 2004. Model-driven Web usage analysis for the evaluation of Web application quality. J. Web Eng. 3, 2, 124--152.
 
42
Gackowski, Z. 2006. Redefining information quality: the operations management approach. In Proceedings of the 11th International Conference on Information Quality (ICIQ). 399--419.
 
43
Hammer, M. 1990. Reengineering work: Don't automate, obliterate. Harvard Bus. Rev. 104--112.
 
44
Hammer, M. and Champy, J. 2001. Reengineering the Corporation: A Manifesto for Business Revolution, Harper Collins.
 
45
46
47
 
48
Istat. 2004. Guidelines for the data quality improvement of localization data in public administration (in Italian). www.istat.it
 
49
 
50
 
51
Kerr, K. and Norris, T. 2004. The development of a healthcare data quality framework and strategy. In Proceedings of the 9th International Conference on Information Quality.
 
52
 
53
Kovac, R. and Weickert, C. 2002. Starting with quality: Using TDQM in a start-up organization. In Proceedings of the 7th International Conference on Information Quality (ICIQ). Boston, 69--78.
 
54
55
 
56
Liu, L. and Chi, L. 2002. Evolutionary data quality. In Proceedings of the 7th International Conference on Information Quality.
 
57
Long, J. and Seko, C. April 2005. A cyclic-hierarchical method for database data-quality evaluation and improvement. In Advances in Management Information Systems-Information Quality Monograph (AMIS-IQ) Monograph, R. Wang, E. Pierce, S. Madnick, and Fisher C.W.
 
58
 
59
Lyman, P. and Varian, H. R. 2003. How much information. http://www.sims.berkeley.edu/how-much-info-2003.
60
 
61
Mecca, G., Merialdo, P., Atzeni, P., and Crescenzi, V. 1999. The (short) araeneus guide to Web site development. In Proceedings of the 2nd International Workshop on the Web and Databases (WebDB) Conjunction with Sigmod.
 
62
 
63
Muthu, S., Withman, L., and Cheraghi, S. H. 1999. Business process re-engineering : a consolidated methodology. In Proceedings of the 4th annual International Conference on Industrial Engineering Theory, Applications and Practice.
 
64
Nadkarni, P. 2006. Delivering data on time: The assurant health case. In Proceedings of the 11th International Conference on Information Quality.
 
65
 
66
Nelson, J., Poels, G., Genero, M., and Piattini, Eds. 2003. Proceedings of the 2nd International Workshop on Conceptual Modeling Quality (IWCMQ). Lecture Notes in Computer Science, vol. 2814, Springer.
 
67
Oakland, J. 1989. Total Quality Management. Springer.
 
68
Office of Management and Budget. 2006. Information quality guidelines for ensuring and maximizing the quality, objectivity, utility, and integrity of information disseminated by agencies. http://www.whitehouse.gov/omb/fedreg/reproducible.html.
 
69
Pernici, B. and Scannapieco, M. 2003. Data quality in Web information systems. J. Data Semant. 1, 48--68.
70
 
71
 
72
Rahm, E., Thor, A., Aumüller, D., Hong-Hai, D., Golovin, N., and Kirsten, T. June 2005. iFuice information fusion utilizing instance correspondences and peer mappings. In Proceedings of the 8th International Workshop on the Web and Databases (WebDB). located with SIGMOD.
 
73
 
74
75
 
76
 
77
Scannapieco, M., Pernici, B., and Pierce, E. 2002. IP-UML: Towards a Methodology for Quality Improvement based on the IP-MAP Framework. In Proceedings of the 7th International Conference on Information Quality (ICIQ). Boston.
 
78
Scannapieco, M., Pernici, B., and Pierce, E. 2005. IP-UML: A methodology for quality improvement-based on IP-MAP and UML. In Information Quality, Advances in Management Information Systems, Information Quality Monograph (AMIS-IQ), R. Wang, E. Pierce, S. Madnik, and C. Fisher, Eds.
 
79
Sessions, V. 2007. Employing the TDQM methodology: An assessment of the SC SOR. In Proceedings of the 12th International Conference on Information Quality. 519--537.
 
80
Shankaranarayan, G., Wang, R. Y., and Ziad, M. 2000. Modeling the manufacture of an information product with IP-MAP. In Proceedings of the 6th International Conference on Information Quality (ICIQ 2000). Boston.
 
81
Shankaranarayanan, G. and Wang, R. 2007. IPMAP: Current state and perspectives. In Proceedings of the 12th International Conference on Information Quality.
 
82
Sheng, Y. 2003. Exploring the mediating and moderating effects of information quality on firm's endeavour on information systems. In Proceedings of the 8th International Conference on Information Quality 2003 (ICIQ). 344--352.
 
83
Sheng, Y. and Mykytyn, P. 2002. Information technology investment and firm performance: A perspective of data quality. In Proceedings of the 7th International Conference on Information Quality (ICIQ). DC, 132--141.
 
84
Stoica, M., Chawat, N., and Shin, N. 2003. An investigation of the methodologies of business process reengineering. In Proceedings of Information Systems Education Conference.
 
85
Su, Y. and Jin, Z. 2004. A methodology for information quality assessment in the designing and manufacturing processes of mechanical products. In Proceedings of the 9th International Conference on Information Quality (ICIQ). 447--465.
 
86
US Department of Defense. 1994. Data administration procedures. DoD rep. 8320.1-M.
 
87
 
88
89
90
 
91
 
92
World Wide Web Consortium. www.w3.org/WAI/. Web accessibility initiative.
 
93
Zachman, J. 2006. Zachman institute for framework advancement (ZIFA). www.zifa.com.

Collaborative Colleagues:
Carlo Batini: colleagues
Cinzia Cappiello: colleagues
Chiara Francalanci: colleagues
Andrea Maurino: colleagues