Self evaluating generalisation algorithms for the derivation of multi-scale products from UKBORDERS data of the census
The aim of the research was to address the problems of rapid dissemination of large volumes of geographic data over the internet. Specifically, ways of reducing the volume of data that is transmitted in response to a request for geographic information. Data volume reduction is required to speed transmission, and to facilitate rapid analysis and display. The research is concerned with the development of self evaluating algorithms for automating this process that adhere to strict quality controls governing the location precision of the data, and completeness of information associated with each location. Such algorithms obviate the need for human intervention which is time consuming and often offers no guarantee of a quality assured result. The research was undertaken in support of the UKBORDERS on-line access system for the 2001 census digital boundary data (jointly supported by ESRC and JISC) and is in collaboration with the Data Library of the University of Edinburgh. Its success is critical to the broad uptake and use of 2001 census digitised boundary data and in the presentation and analysis of information at a range of scales and themes. The research is fundamental to the broader issues of data integration, for example in the creation of national databases such as NLIS and ScotLIS where it will be necessary to integrate data sources of differing scale, resolution and information content.