SciDB-based Framework for Efficient Satellite Data Storage and Query based on Dynamic Atmospheric Event Trajectory

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F15%3A00238159" target="_blank" >RIV/68407700:21240/15:00238159 - isvavai.cz</a>

Result on the web

<a href="http://www.cse.buffalo.edu/~chandola/workshops/bigspatial-2015/program.html" target="_blank" >http://www.cse.buffalo.edu/~chandola/workshops/bigspatial-2015/program.html</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

SciDB-based Framework for Efficient Satellite Data Storage and Query based on Dynamic Atmospheric Event Trajectory

Original language description

Current research in climate informatics focuses mainly on the development of novel (machine learning, data mining, or statistical) techniques to analyze climate data (e.g. model, in-situ, or satellite) or to make prediction based on these climate data. One important component missing from this analysis workflow is data management that allows efficient and flexible data retrieval, (ease of) reproducibility, and the (ease of) techniques reuse on user-defined data subsets or other data. In this paper, we describe our preliminary investigation on the utilization of the distributed array-based database management system, SciDB, to support data-driven climate science research. We focus on modeling and generating indices that allow effective execution of various spatiotemporal queries on satellite data. Moreover, we demonstrate fast and accurate data retrieval based on user-specified trajectories from the SciDB database containing tropical cyclone trajectories and the complete ten-year QuikSCAT ocean surface wind fields satellite data. Our preliminary work indicates the feasibility of the arraybased technology for multiple satellite data storage, query, and analysis. Towards this end, a successful deployment of SciDB-based data storage can facilitate the use of data from multiple satellites for climate and weather research.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 4th International ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data

ISBN

978-1-4503-3974-2

ISSN

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e-ISSN

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Number of pages

8

Pages from-to

7-14

Publisher name

ACM

Place of publication

New York

Event location

Bellevue, WA, USA

Event date

Nov 3, 2015

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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