The information quality of databases

Encyclopedia of Database Technologies and Applications

Volumn , Issue , 2005, Pages 281-285

  Chengalur Smith, Indushobha ^a   Neely, M Pamela ^b   Tribunella, Thomas ^b  

^a STATE UNIVERSITY OF NEW YORK   (United States)

^b ROCHESTER INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 51549083988     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59140-560-3.ch048     Document Type: Chapter

References (21)

1. Adam, N. R., & Wortmann, J. C. (1989). Security control methods for statistical databases: A comparative study. ACM Computing Surveys, 21(4), 515-556.
2. Ballou, D. P., Chengalur-Smith, I. N., & Wang, R. Y. (2004). Quality estimation for information products in relational database environments.
3. Ballou, D. P., & Pazer, H. L. (1995). Designing information systems to optimize the accuracy timeliness tradeoffs. Information Systems Research, 6(1), 51-72.
4. Ballou, D. B., Wang, R. Y., Pazer, H. L., & Tayi, G. K. (1998, April). Modeling information manufacturing systems to determine information product quality. Management Science, 44(4), 462-484.
5. Chengalur-Smith, I. N., Ballou, D. P., & Pazer, H. L. (1999). The impact of data quality information on decision making: An exploratory analysis. IEEE Transactions on Knowledge and Data Engineering, 11(6), 853-864.
6. DeLone & McLean. (2003). The DeLone and McLean model of information systems success: A ten year update. Journal of Management Information Systems, 19(4), 9-30.
7. Fisher, C., Chengalur-Smith, I. N., & Ballou, D. P. (2003).The impact of experience and time on the use of data quality information in decision making. Information Systems Research, 14(2), 170-188.
8. Lee, Y., & Strong, D. (2003). Knowing why about data processes and data quality. Journal of Management Information Systems, 20(3), 13-39.
9. Levin, R. (1998). Meta matters. Information Week, 18-19.
10. Muralidhar, K, Parsa, R., & Sarathy, R. (1999). A general additive data perturbation method for database security. Management Science, 45(10), 1399-1415.
11. Neely, P. (1998). Data quality tools for data warehousing: A small sample survey. Proceedings of the International Conference on Information Quality, Cambridge, MA.
12. Pipino, L., Lee, Y. W., & Wang, R. Y. (2002). Data quality assessment. Communications of the ACM, 45(4), 211-218.
13. Platinum Technology. (2000). Putting metadata to work in the warehouse. Computer Associates White Paper.
14. Shankaranarayan, G., Ziad, M., & Wang, R. Y. (2003). Managing data quality in dynamic decision environment: An information product approach. Journal of Database Management, 14(4).
15. Stephanidis, C. (2001). Adaptive techniques for universal access. User Modeling and User-Adapted Interaction, 11, 159-179.
16. Strong, D. M., Lee, Y. W., & Wang, R. W. (1997). 10 potholes in the road to information quality. Computer, 30(8), 38-46.
17. Tseng, H., & Fogg, B. J. (1999). Credibility and computing technology. Communications of the ACM, 42(5), 39-44.
18. Wang, R. Y., Lee, Y. W., Pipino, L., & Strong, D. M. (1998). Manage your information as a product. Sloan Management Review, 39(4), 95-105.
19. Wang, R. Y. & Strong, D. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5-34.
20. Wathen, C. N., & Burkell, J. (2002). Believe it or not: Factors influencing credibility on the Web. Journal of the American Society for Information Science and Technology, 53(2), 134-144.
21. Wixom, B. H., & Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25(1), 17-41.