Semi-structured data has become prevalent with the growth of the Internet and other on-line information repositories. Many organizational databases are presented on the web as semi-structured data. Designing a “good” semi-structured database is increasingly crucial to prevent data redundancy, inconsistency and updating anomalies. In this paper, we define a semi-structured schema graph and identify the various anomalies that may occur in the graph. A normal form for semi- structured schema graph, S3-NF, is proposed. We present two approaches to design S3-NF database, namely, restructuring by decomposition and the ER approach. The first approach consists of a set of rules to decompose a semi-structured schema graph into S3-NF. The second approach uses the ER model to remove anomalies at the semantic level.
CITATION STYLE
Lee, S. Y., Lee, M. L., Ling, T. W., & Kalinichenko, L. A. (1999). Designing good semi-structured databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1728, pp. 131–145). Springer Verlag. https://doi.org/10.1007/3-540-47866-3_9
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