Schema Evolution publication categorizer

Whenever transformation of data is used to bridge the gap of different data formats, and a query is given in the destination format, query reformulation can speed up the transformation of data. We achieve this speed-up in transformation when only the required data segment, described by the computed reformulated query, is transformed. Whenever the required section of data is not too large, query reformulation allows transformation on demand, even when the input data is large. Among other things, using query reformulation avoids problems of replication (especially synchronization problems), saves time and memory space for transformation and, in distributed scenarios, reduces the size of transmitted documents and transmission time. Whereas query reformulation is used in traditional relational databases, there has not been any complete query reformulation approach applicable to all of the most widely used XML standards
of the W3C, most notably XPath, XQuery and XSLT. Within this paper, we outline a global approach to implement query reformulation for each of the XML standards XPath, XQuery and XSLT.