Large spatial datasets: Present Challenges, future opportunities
Global Proceedings Repository
View Archive Info| Field | Value | |
| Title |
Large spatial datasets: Present Challenges, future opportunities
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| Creator |
Grace L. Samson
Joan Lu Qiang Xu |
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| Description |
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.
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| Publisher |
Int'l Conference on Change, Innovation, Informatics and Disrurptuive Technology
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| Contributor |
—
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| Date |
2016-12-17 20:55:59
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| Type |
Peer-reviewed Paper
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| Format |
application/pdf
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| Identifier |
http://proceedings.sriweb.org/repository/index.php/ICCIIDT/icciidtt_london/paper/view/24
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| Source |
Int'l Conference on Change, Innovation, Informatics and Disrurptuive Technology; ICCIIDT London - UK
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| Language |
en
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| Rights |
Authors who submit to this conference agree to the following terms: a) Authors retain copyright over their work, while allowing the conference to place this unpublished work under a Creative Commons Attribution License, which allows others to freely access, use, and share the work, with an acknowledgement of the work's authorship and its initial presentation at this conference. b) Authors are able to waive the terms of the CC license and enter into separate, additional contractual arrangements for the non-exclusive distribution and subsequent publication of this work (e.g., publish a revised version in a journal, post it to an institutional repository or publish it in a book), with an acknowledgement of its initial presentation at this conference. c) In addition, authors are encouraged to post and share their work online (e.g., in institutional repositories or on their website) at any point before and after the conference. |
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