Hart, Robert2017-12-042017-12-0420172017-12-04http://hdl.handle.net/1828/8832The Kimball methodology, often referred to as dimensional modelling, is well established in data warehousing and business intelligence as a highly successful means for turning data into information. Yet weaknesses exist in the Kimball approach that make it difficult to rapidly extend or interrelate dimensional models in complex business areas such as Health Care. This Thesis looks at the development of a methodology that will provide for the rapid extension and interrelation of Kimball dimensional models. This is achieved through the use of techniques similar to those employed in the semantic web. These techniques allow for rapid analysis and insight into highly variable data which previously was difficult to achieve.enAvailable to the World Wide WebKimballStar SchemaHealth InformationBusiness IntelligenceData WarehouseRDF TripletsDimensional ModelHealth Data ResearchThesisHart, R., Kuo, A. M. (2017). IOS Press Ebooks - Better Data Quality for Better Healthcare Research Results – A Case Study. (2017). Ebooks.iospress.nl. Retrieved 18 July 2017, from http://ebooks.iospress.nl/volumearticle/46158Hart, R., Kuo, A. M. (2016). Meeting Health Care Research Needs in a Kimball Integrated Data Warehouse, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), Montreal, QC, 2016, pp. 697-705. doi: 10.1109/DSAA.2016.91