Data is an important asset used for various organizational activities. Poor data quality could have severe implications for information systems security in organizations. In this paper, data is viewed as embodied in the concept of signs. This paper identifies dimensions of data quality by using semiotics as a theoretical basis. We argue that the nature and scope of data quality dimensions changes as we move between different semiotic levels. An understanding of these changes is essential for ensuring information systems security.
CITATION STYLE
Tejay, G., Dhillon, G., & Chin, A. G. (2005). Data Quality Dimensions for Information Systems Security: A Theoretical Exposition (Invited Paper). IFIP Advances in Information and Communication Technology, 193, 21–39. https://doi.org/10.1007/0-387-31167-x_2
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