The key advantages of a well-designed multidimensional database is its ability to allow as many users as possible across an organisation to simultaneously gain access and view of the same data. Large spatial datasets evolve from scientific activities (from recent days) that tends to generate large databases which always come in a scale nearing terabyte of data size and in most cases are multidimensional. In this paper, we look at the issues pertaining to large spatial datasets; its feature (for example views), architecture, access methods and most importantly design technologies. We also looked at some ways of possibly improving the performance of some of the existing algorithms for managing large spatial datasets. The study reveals that the major challenges militating against effective management of large spatial datasets is storage utilization and computational complexity (both of which are characterised by the size of spatial big data which now tends to exceeds the capacity of commonly used spatial computing systems owing to their volume, variety and velocity). These problems fortunately can be combated by employing functional programming method or parallelization techniques.
|Number of pages||14|
|Publication status||Published - 24 Feb 2017|
|Event||International Conference on Change, Innovation, Informatics and Disruptive Technology - Sandell St, London, United Kingdom|
Duration: 11 Oct 2016 → 12 Oct 2016
http://sriweb.org/londonconf/ (Link to Conference Website)