A Comparative Study of Data Transformations for Efficient XML and JSON Data Compression. An In-Depth Analysis of Data Transformation Techniques, including Tag and Capital Conversions, Character and Word N-Gram Transformations, and Domain-Specific Data Transforms using SMILES Data as a Case Study

XML is a widely used data exchange format. The verbose nature of XML leads to the requirement to efficiently store and process this type of data using compression. Various general-purpose transforms and compression techniques exist that can be used to transform and compress XML data. More compact alternatives to XML data have been developed, namely JSON due to the verbosity of XML data. Similarly, there is a requirement to efficiently store and process SMILES data used in Chemoinformatics. General-purpose transforms and compressors can be used to compress this type of data to a certain extent, however, these techniques are not specific to SMILES data. The primary contribution of this research is to provide developers that use XML, JSON or SMILES data, with key knowledge of the best transformation techniques to use with certain types of data, and which compression techniques would provide the best compressed output size and processing times, depending on their requirements. The main study in this thesis, investigates the extent of which using data transforms prior to data compression can further improve the compression of XML and JSON data. It provides a comparative analysis of applying a variety of data transform and data transform variations, to a number of different types of XML and JSON equivalent datasets of various sizes, and applying different general-purpose compression techniques over the transformed data. A case study is also conducted, to investigate data transforms prior to compression to improve the compression of data within a data-specific domain.

Grantor dc:publisher.institution

University of Bradford

Year dc:date.issued

2017

Author dc:creator

• Scanlon, Shagufta A.

Advisors dc:contributor.advisor

• Ridley, Mick J.
• Cullen, Andrea J.

• XML; JSON; Data; Compression; Decompression; Transformation; N-Grams; SMILES

Statement dc:rights

• <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10454/14180

OAI identifier oai:identifier

oai:bradscholars.brad.ac.uk:10454/14180