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Multigranular spatio-temporal models: implementation challenges

Authors:

Elena Camossi,

Michela Bertolotto,

Elisa BertinoAuthors Info & Claims

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

Article No.: 63, Pages 1 - 4

https://doi.org/10.1145/1463434.1463508

Published: 05 November 2008 Publication History

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Abstract

Multiple granularities provide an essential support for extracting significant knowledge from spatio-temporal datasets at different levels of details. They enable to zoom-in and zoom-out spatio-temporal datasets, thus enhancing the data modelling exibility and improving the analysis of information. In this paper we investigate the implementation issues arising when a data model and a query language are enriched with spatio-temporal multigranularity. We introduce appropriate representations for space and time dimensions, granularities, granules, and multi-granular values. Finally, we discuss how multigranular spatio-temporal conversions affect data usability and how such important property may be guaranteed.

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Cited By

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Arregui HOtaegui OArbelaitz O(2020)Data-Driven Representation Model of Urban Movement SpaceProceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis10.1145/3397056.3397061(24-28)Online publication date: 15-Apr-2020
https://dl.acm.org/doi/10.1145/3397056.3397061
Chen MGao SZhou JWang XOssowski S(2016)Converting spatiotemporal data among multiple granularity systemsProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851893(1008-1010)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851893
Chen MGao SWang X(2016)Converting spatiotemporal data Among heterogeneous granularity systems2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ-IEEE.2016.7737795(984-992)Online publication date: Jul-2016
https://doi.org/10.1109/FUZZ-IEEE.2016.7737795
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Index Terms

Multigranular spatio-temporal models: implementation challenges
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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Information & Contributors

Information

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

Publication History

Published: 05 November 2008

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Poster

Funding Sources

Irish Research Council for Science, Engineering and Technology

Conference

GIS '08

Sponsor:

Microsoft
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 220 of 1,116 submissions, 20%

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Cited By

View all

Arregui HOtaegui OArbelaitz O(2020)Data-Driven Representation Model of Urban Movement SpaceProceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis10.1145/3397056.3397061(24-28)Online publication date: 15-Apr-2020
https://dl.acm.org/doi/10.1145/3397056.3397061
Chen MGao SZhou JWang XOssowski S(2016)Converting spatiotemporal data among multiple granularity systemsProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851893(1008-1010)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851893
Chen MGao SWang X(2016)Converting spatiotemporal data Among heterogeneous granularity systems2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ-IEEE.2016.7737795(984-992)Online publication date: Jul-2016
https://doi.org/10.1109/FUZZ-IEEE.2016.7737795
Longo JMedeiros C(2013)Providing multi-scale consistency for multi-scale geospatial dataProceedings of the 25th International Conference on Scientific and Statistical Database Management10.1145/2484838.2484867(1-12)Online publication date: 29-Jul-2013
https://dl.acm.org/doi/10.1145/2484838.2484867
Campelo CBennett B(2012)Geographical Process RepresentationUniversal Ontology of Geographic Space10.4018/978-1-4666-0327-1.ch004(73-96)Online publication date: 2012
https://doi.org/10.4018/978-1-4666-0327-1.ch004
Bertino ECamossi EBertolotto M(2009)Multi-granular spatio-temporal object modelsProceedings of the Second international conference on Object databases10.5555/1883713.1883721(132-148)Online publication date: 1-Jul-2009
https://dl.acm.org/doi/10.5555/1883713.1883721

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Formal and conceptual modeling of spatio-temporal granularities

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