TY - GEN
T1 - A SciDB-based framework for efficient satellite data storage and query based on dynamic atmospheric event trajectory
AU - Krčál, Luboš
AU - Ho, Shen Shyang
N1 - Publisher Copyright:
Copyright 2015 ACM.
PY - 2015/11/3
Y1 - 2015/11/3
N2 - 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 array-based 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.
AB - 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 array-based 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.
UR - http://www.scopus.com/inward/record.url?scp=84982798840&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982798840&partnerID=8YFLogxK
U2 - 10.1145/2835185.2835190
DO - 10.1145/2835185.2835190
M3 - Conference contribution
AN - SCOPUS:84982798840
T3 - Proceedings of the 4th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2015
SP - 7
EP - 14
BT - Proceedings of the 4th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2015
A2 - Chandola, Varun
A2 - Vatsavai, Ranga Raju
PB - Association for Computing Machinery, Inc
T2 - 4th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2015
Y2 - 3 November 2015
ER -