Abstract
Quality information and information quality management in an organization is essential for effective operations and decision-making. The proliferation of data warehouses to support decision-making further highlights an organization’s vulnerability with respect to poor data quality, especially given the widely disparate data sources, contexts, users, and data uses characterizing data warehouses and the much less predictable data usage involved in decision-making as compared to business operations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ballou, D., Wang, R.Y., Pazer, H. and Tayi, G.K. (1998). Modeling Information Manufacturing Systems to Determine Information Product Quality, Journal of Management Science 44(4): 462–484.
Barnes, S.J. and Vidgen, R.T. (2002). An Integrative Approach to the Assessment of e-Commerce Quality, Journal of Electronic Commerce Research 3(3): 114–127.
Barnouw, E. (ed.) (1989). International Encyclopedia of Communications, Oxford: Oxford University Press.
DeLone, W.H. and McLean, E.R. (2003). The DeLone and McLean Model of Information System Success: A ten-year update, Journal of Management Information Systems 19(4): 9–30.
English, L. (1999). Improving Data Warehouse and Business Information Quality, New York: John Wiley & Sons, Inc.
Eppler, M.J. (2001). The Concept of Information Quality: An interdisciplinary evaluation of recent information quality frameworks, Studies in Communication Sciences 1: 167–182.
Gendron, M. and Shanks, G. (2003). The Categorical Information Quality Framework (CIQF): A critical assessment and replication study, in Proceedings of the Pacific-Asia Conference on Information Systems, (Adelaide, Australia, 2003), Adelaide, South Australia: University of South Australia, 1–13.
Kahn, B.K., Strong, D.M. and Wang, R.Y. (1997). A Model for Delivering Quality Information as Product and Service, in Proceedings of Conference on Information Quality, (Massachusetts Institute of Technology, Cambridge, MA, USA, 1997), Cambridge, MA, USA: Massachussets Institute of Technology, 80–94.
Kahn, B.K., Strong, D.M. and Wang, R.Y. (2002). Information Quality Benchmarks: Product and service performance, Communications of the ACM 45(4): 184–192.
Krogstie, J. (2001). A Semiotic Approach to Quality in Requirements Specifications, in: Proceedings of IFIP 8.1 Working Conference on Organizational Semiotics, (Montreal, Canada 2001), London: Chapman and Hall, 231–249.
Krogstie, J., Lindland, O.I. and Sindre, G. (1995). Defining Quality Aspects for Conceptual Models, in Proceedings of IFIP8.1 working conference on Information Systems Concepts (ISCO3): Towards a consolidation of views, (Marburg, Germany, 1995), Berlin: Springer, 216–231.
Krueger, R.A. (1994). Focus Groups: A practical guide for research, Thousand Oaks, CA: Sage.
Lee, Y.W., Strong, D.M., Kahn, B.K. and Wang, R.Y. (2002). AIMQ: A methodology for information quality assessment, Information and Management 40: 133–146.
Morris, C. (1938). Foundations of the Theory of Signs, in International Encyclopedia of Unified Science, Vol. 1, London: University of Chicago Press.
Pierce, C.S. (1931–1935). Collected Papers, Cambridge, MA: Harvard University Press.
Price, R. and Shanks, G. (2004). A Semiotic Information Quality Framework, in Proceedings of the IFIP International Conference on Decision Support Systems (DSS2004), (Prato, Italy, 2004), Melbourne, Victoria, Australia: Monash University, 658–672.
Price, R. and Shanks, G. (2005). Empirical Refinement of a Semiotic Information Quality Framework, in Proceedings of Hawaii International Conference on System Sciences (HICSS38), (Big Island, Hawaii, USA, 2005); Silver Spring, MD: IEEE Computer Society Press, 1–10.
Redman, T.C. (1996). Data Quality for the Information Age, Boston, MA: Artech House.
Shanks, G. and Darke, P. (1998). Understanding Data Quality in Data Warehousing: A semiotic approach, in Proceedings of the MIT Conference on Information Quality, (Boston, MA, USA, 1998), Cambridge, MA, USA: Massachusetts Institute of Technology, 247–264.
Straub, D., Boudreau, M.C. and Gefen, D. (2004). Validation Guidelines of IS Positivist Research, Communications of the Association for Information Systems 13: 380–426.
Stamper, R. (1991). The Semiotic Framework for Information Systems Research, in: Nissen H, Klein H and Hirschheim R (eds.) Information Systems Research: Contemporary Approaches and Emergent Traditions, Amsterdam: North-Holland.
Wand, Y. and Wang, R.Y. (1996). Anchoring Data Quality Dimensions in Ontological Foundations, Communications of the ACM 39(11): 86–95.
Wand, Y. and Weber, R. (1995). On the Deep Structure of Information Systems, Information Systems Journal 5: 203–223.
Wang, R.Y. and Strong, D.M. (1996). Beyond Accuracy: What data quality means to data consumers, Journal of Management Information Systems 12(4): 5–34.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Association for Information Technology Trust
About this chapter
Cite this chapter
Price, R., Shanks, G. (2016). A Semiotic Information Quality Framework: Development and Comparative Analysis. In: Willcocks, L.P., Sauer, C., Lacity, M.C. (eds) Enacting Research Methods in Information Systems. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-29272-4_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-29272-4_7
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-319-29271-7
Online ISBN: 978-3-319-29272-4
eBook Packages: Business and ManagementBusiness and Management (R0)