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Finding my CRS: a systematic way of identifying CRSs

Authors:

Piero Campalani,

Dimitar MisevAuthors Info & Claims

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

Pages 71 - 78

https://doi.org/10.1145/2424321.2424332

Published: 06 November 2012 Publication History

Abstract

In the era of Big Data, being able to work with multidimensional arrays in a robust and consistent manner as the number and variety of dimensions increase, is just as important as being able to handle the large volumes inherent to this type of data. Usually, array analytics is carried out to extract meaningful information for further applications, e.g. slicing and subsetting. While domain-specific dimensions, which are beyond spatio-temporal, underlie rich domain anchor semantics, assigning consistent dimension schema for Points Of Interest (POI) across multidisciplinary data sets is challenging. New compositions of CRSs need to be constructed on the fly by a heterogeneous community with different backgrounds and applications in mind, consequently, linking dimensions via different resolvers to drive away dimension fragments from high-dimensional spaces. We propose to identify dimensions via a linked resolver approach. Such an approach allows CRSs to be referred to and looked up across multidisciplinary applications. Finally, we present a planetary use case, and specification- and scenario-based testing results to validate our approach.

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Cui ZLuo YYu JWei D(2024)A Tiled EO Data Cube Based on BeiDou Grid2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS)10.1109/ICGMRS62107.2024.10581066(252-255)Online publication date: 12-Apr-2024
https://doi.org/10.1109/ICGMRS62107.2024.10581066
Broniszewska MDaszczuk WCzejdo D(2024)Anonymization of Bids in Blockchain Auctions Using Zero-Knowledge ProofSystem Dependability - Theory and Applications10.1007/978-3-031-61857-4_2(19-28)Online publication date: 14-Jun-2024
https://doi.org/10.1007/978-3-031-61857-4_2
Yu JYang YTong RCui Z(2022)A Study to Manage Multidimensional Imagery Data in a Spatial Variable DatacubeIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium10.1109/IGARSS46834.2022.9883050(4078-4081)Online publication date: 17-Jul-2022
https://doi.org/10.1109/IGARSS46834.2022.9883050
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Index Terms

Finding my CRS: a systematic way of identifying CRSs
1. Applied computing
  1. Physical sciences and engineering
    1. Astronomy
    2. Earth and atmospheric sciences
2. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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Information

Published In

cover image ACM Conferences

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

November 2012

642 pages

ISBN:9781450316910

DOI:10.1145/2424321

General Chairs:
Isabel Cruz
University of Illinois at Chicago
,
Craig Knoblock
University of Southern California
,
Program Chairs:
Peer Kröger
Ludwig-Maximilians-Universität München, Germany
,
Egemen Tanin
University of Melbourne, Australia
,
Peter Widmayer
ETH Zürich, Switzerland

Copyright © 2012 ACM.

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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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2012

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SIGSPATIAL'12

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SIGSPATIAL

SIGSPATIAL'12: SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems

November 6 - 9, 2012

Redondo Beach, California

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

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Cited By

Cui ZLuo YYu JWei D(2024)A Tiled EO Data Cube Based on BeiDou Grid2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS)10.1109/ICGMRS62107.2024.10581066(252-255)Online publication date: 12-Apr-2024
https://doi.org/10.1109/ICGMRS62107.2024.10581066
Broniszewska MDaszczuk WCzejdo D(2024)Anonymization of Bids in Blockchain Auctions Using Zero-Knowledge ProofSystem Dependability - Theory and Applications10.1007/978-3-031-61857-4_2(19-28)Online publication date: 14-Jun-2024
https://doi.org/10.1007/978-3-031-61857-4_2
Yu JYang YTong RCui Z(2022)A Study to Manage Multidimensional Imagery Data in a Spatial Variable DatacubeIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium10.1109/IGARSS46834.2022.9883050(4078-4081)Online publication date: 17-Jul-2022
https://doi.org/10.1109/IGARSS46834.2022.9883050
Yang YYu JTong R(2021)Research on Domain Variable Identification among Different Data Cubes2021 28th International Conference on Geoinformatics10.1109/IEEECONF54055.2021.9687644(1-4)Online publication date: 3-Nov-2021
https://doi.org/10.1109/IEEECONF54055.2021.9687644
Tan ZYue PGong J(2017)An Array Database Approach for Earth Observation Data Management and ProcessingISPRS International Journal of Geo-Information10.3390/ijgi60702206:7(220)Online publication date: 19-Jul-2017
https://doi.org/10.3390/ijgi6070220
Andrejev AMisev DBaumann PRisch T(2015)Spatio-Temporal Gridded Data Processing on the Semantic WebProceedings of the 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS)10.1109/DSDIS.2015.109(38-45)Online publication date: 11-Dec-2015
https://dl.acm.org/doi/10.1109/DSDIS.2015.109
Baumann PMazzetti PUngar JBarbera RBarboni DBeccati ABigagli LBoldrini EBruno RCalanducci ACampalani PClements ODumitru AGrant MHerzig PKakaletris GLaxton JKoltsida PLipskoch KMahdiraji AMantovani SMerticariu VMessina AMisev DNatali SNativi SOosthoek JPappalardo MPassmore JRossi ARundo FSen MSorbera VSullivan DTorrisi MTrovato LVeratelli MWagner S(2015)Big Data Analytics for Earth Sciences: the EarthServer approachInternational Journal of Digital Earth10.1080/17538947.2014.10031069:1(3-29)Online publication date: 2-Mar-2015
https://doi.org/10.1080/17538947.2014.1003106
Oosthoek JFlahaut JRossi ABaumann PMisev DCampalani PUnnithan V(2014)PlanetServer: Innovative approaches for the online analysis of hyperspectral satellite data from MarsAdvances in Space Research10.1016/j.asr.2013.07.00253:12(1858-1871)Online publication date: Jun-2014
https://doi.org/10.1016/j.asr.2013.07.002
Campalani PMisev DBeccati ABaumann P(2013)Making Time Just Another Axis in Geospatial ServicesProceedings of the 2013 20th International Symposium on Temporal Representation and Reasoning10.1109/TIME.2013.24(133-140)Online publication date: 26-Sep-2013
https://dl.acm.org/doi/10.1109/TIME.2013.24

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