Spatial Cluster Analysis by the Adleman-Lipton DNA Computing Model and Flexible Grids

Spatial cluster analysis is an important data-mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann’s computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis based on DNA computing and a grid technique. We will adopt the Adleman-Lipton model and then design a flexible grid algorithm. Examples are given to show the effect of the algorithm. The new clustering technique provides an alternative for traditional cluster analysis

Creating an open geodemographic classification using the UK Census of the Population

The 2011 Area Classification for Output Areas (2011 OAC) is a new open geodemographic classification of the UK based on 2011 UK Census data. The 2011 OAC, created in partnership with the Office for National Statistics (ONS), supersedes the 2001 Area Classification for Output Areas (2001 OAC) to provide the most current open geodemographic view of the UK. The 2001 OAC was widely used in academia, local government and by commercial organisations, but its reliance on data from the 2001 UK Census has led to a perceived degradation of reliability over time and a decline in users. The release of the 2011 UK Census data provided the opportunity to create a 2011 OAC which could address some of the acknowledged flaws of the 2001 OAC, such as the methods used for data handling, to create a more robust methodology. The publication of this methodology with accompanying documentation, in addition to utilising open-source software, guarantees the reproducibility of the 2011 OAC; with an additional benefit of the methodology being able to act as a template for future bespoke open geodemographic classifications. Open geodemographic classifications, unlike those provided by commercial organisations, have historically been unable to utilise ancillary data sources to enrich and update their systems. This research proposes an alternative approach; utilising the limited range of Open Data sources made available regularly at the small granular level to create uncertainty indicators. These indicators allow areas of uncertainty that develop over time within the classification’s geodemographic assignment to be identified; allowing users the opportunity to take compensatory action. This project delivered a new open geodemographic classification of the UK. The methodological advances, use of open source software and ability to assess the temporal stability of geodemographic assignments mean the 2011 OAC can be considered a step forward for open geodemographics