XML Data in (Object-) Relational Databases

As XML has become a standard for data representation, it is inevitable to propose and implement techniques for e±cient managing of XML documents. A natural alternative is to exploit features and functions of (object-)relational database management systems, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an appropriate XML-to-relational mapping strategy. In this thesis we focus on further enhancing of current most e±cient XML-to-relational storage strategies { so-called adaptive methods. Firstly, we perform a detailed analysis of existing works and especially remaining open issues. Secondly, we propose their enhancing which can be characterized as a hybrid user-driven adaptive mapping strategy, i.e. a combination of so-called user-driven and adaptive methods. In the enhancing we focus especially on deeper exploitation of user-given information, i.e. schema annotations, and we propose an approach which enables to identify new annotation candidates and thus to help users to nd a more appropriate mapping strategy. For this purpose we propose a similarity measure which focuses mainly on structural similarity of the given data and an algorithm which enables reasonable tuning of its parameters on the basis of results of statistical analysis of..