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Efficient data modeling and querying system for multi-dimensional spatial data

Authors:

Wei Li,

Cindy X. ChenAuthors Info & Claims

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

Article No.: 58, Pages 1 - 4

https://doi.org/10.1145/1463434.1463503

Published: 05 November 2008 Publication History

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Abstract

Multi-dimensional spatial data are obtained when a number of data acquisition devices are deployed at different locations to measure a certain set of attributes of the study subject. How to manipulate these spatial data remains a challenge to the database community, especially when the spatial locations are represented in 3D. In this work, we establish a data model to handle multi-dimensional spatial data with three spatial dimensions. In particular, firstly, a clustering algorithm is applied to group the data set into "point clouds". Secondly, each cloud is considered as a 3D spatial convex object and triangulated into a set of tetrahedrons. Thirdly, all tetrahedron sets are stored in the database and spatial analysis is performed. In this paper, we focus on defining 3D spatial operations and relationships for 3D spatial elements (points, segments, triangles and tetrahedrons), and further applying these operations on 3D spatial objects, where each object is composed of a set of tetrahedrons.

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Cited By

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Soliman HKhan IHussain Y(2022)Learning to transfer knowledge from RDF Graphs with gated recurrent unitsIntelligent Data Analysis10.3233/IDA-21591926:3(679-694)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/IDA-215919
Soliman H(2020)Deep learning based searching approach for RDF graphsPLOS ONE10.1371/journal.pone.023050015:3(e0230500)Online publication date: 23-Mar-2020
https://doi.org/10.1371/journal.pone.0230500
Soliman H(2020)Random Forest Based Searching Approach for RDFIEEE Access10.1109/ACCESS.2020.29801558(50367-50376)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2980155
Show More Cited By

Index Terms

Efficient data modeling and querying system for multi-dimensional spatial data
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Data management systems
    1. Database design and models
  2. Information systems applications
    1. Spatial-temporal systems

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Published In

GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems

November 2008

559 pages

ISBN:9781605583235

DOI:10.1145/1463434

Program Chairs:
Walid G. Aref
Purdue University
,
Mohamed F. Mokbel
University of Minnesota
,
Markus Schneider
University of Florida

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 05 November 2008

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SIGSPATIAL

GIS '08: 16th International Symposium on Advances in Geographic Information Systems

November 5 - 7, 2008

California, Irvine

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Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Soliman HKhan IHussain Y(2022)Learning to transfer knowledge from RDF Graphs with gated recurrent unitsIntelligent Data Analysis10.3233/IDA-21591926:3(679-694)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/IDA-215919
Soliman H(2020)Deep learning based searching approach for RDF graphsPLOS ONE10.1371/journal.pone.023050015:3(e0230500)Online publication date: 23-Mar-2020
https://doi.org/10.1371/journal.pone.0230500
Soliman H(2020)Random Forest Based Searching Approach for RDFIEEE Access10.1109/ACCESS.2020.29801558(50367-50376)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2980155
Pardeshi TKulkarni P(2019)Efficient Retrieval from Multi-dimensional Dataset Based on Nearest KeywordInnovations in Computer Science and Engineering10.1007/978-981-13-7082-3_9(65-71)Online publication date: 19-Jun-2019
https://doi.org/10.1007/978-981-13-7082-3_9
Sampada KAdithya LKavya N(2018)Performance Analysis of Multidimensional Indexing in Keyword SearchProceedings of International Conference on Recent Advancement on Computer and Communication10.1007/978-981-10-8198-9_18(171-184)Online publication date: 19-Apr-2018
https://doi.org/10.1007/978-981-10-8198-9_18
Singh VZong BSingh A(2016)Nearest Keyword Set Search in Multi-Dimensional DatasetsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2015.249254928:3(741-755)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1109/TKDE.2015.2492549

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Modelling gross primary production in semi-arid Inner Mongolia using MODIS imagery and eddy covariance data

Modelling forest stand volume and tree density using Landsat ETM+ data

A data fusion and spatial data analysis approach for the estimation of wheat grain nitrogen uptake from satellite data

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