Indexing and Querying Semistructured Data Views of Relational Database

The most promising and dominant data format for data processing and representing on the Internet is the Semistructured data form termed XML. XML data has no fixed schema; it evolved and is self describing which results in management difficulties compared to, for example relational data. XML queries differ from relational queries in that the former are expressed as path expressions. The efficient handling of structural relationships has become a key factor in XML query processing. It is therefore a major challenge for the database community to design query processing techniques and storage methods that can manage semistructured data efficiently. The main contribution of this paper is querying semistructured data using bitmap to represent path-value relationship and compress the bitmap to save space. The presented bitmap indexing and querying scheme termed BIQS data that stores the element path, token of the word, attribute and document number in a dynamically created matrix structure. We use word, attribute and path dictionaries for the construction of a Bitmap structure. This paper describes an algorithm to query semistructured data in a more time efficient way than is provided by other relational and semistructured query processing techniques. The presented BIQS structure provides storage and query performance improvement due to the compression of semistructured data.