a case study on alternate representations of data structures in xml
XML provides a universal and portable format for document and data exchange. While the syntax and specification of XML makes documents both human readable and machine parsable, it is often at the expense of efficiency when representing simple data structures.We investigate the ``costs'' associated with XML serialization from several resource perspectives: storage, transport, processing and human readability. These experiments are done within the context of a large text-centric service oriented architecture -- IBM's WebFountain project.We find that for several applications, human readable formats outperform binary equivalents, especially in the area of data size, and that the costs of processing encoded binary data often exceeds that of processing terse human readable formats.
data structures xml serialization webfountain compression