Design and development of knowledge-preserving and robust water- marking techniques for digital ownership rights protection of relational databases is an active area of research. In this dissertation, various dis- ciplines have been used to design and develop watermarking techniques which ensure knowledge-preserving and robustness characteristics of wa- termarking techniques by bringing tolerable distortions in the original data. Different parameters are used to define data distortions in terms of information loss as a result of watermarking. The intelligent min- ing techniques and statistical measures have been utilized to define and measure information loss after watermark embedding in the relational databases. The data owner usually defines the usability constraints to control this information loss. These usability constraints in turn iden- tify the available bandwidth for watermark embedding. The watermark decoding accuracy of a watermarking algorithm generally depends on this bandwidth; larger the bandwidth the better the decoding accuracy (watermark robustness) and vice versa. However, this dissertation pro- poses a model to make the watermark decoding accuracy independent of this bandwidth and hence the usability constraints; as a result, max- imum decoding accuracy can be achieved even with very tight usability constraints and minimum data distortions. Such mechanism also helps to preserve the knowledge in the databases to a maximum level; as a consequence, the classification results for such databases are also pre- served after watermark embedding. In the pilot study, empirical study and formal modeling have been used to prove the knowledge-preserving and robustness characteristics of the proposed watermarking techniques for digital right protection.