Parallel Query Support for Multidimensional Data: Inter-object Parallelism

Hahn, Karl; Reiner, Bernd; Höfling, Gabriele; Baumann, Peter

doi:10.1007/3-540-46146-9_81

Cited by 10 publications

(3 citation statements)

References 4 publications

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“…Request rewriting exploits algebraic equivalences to substitute query fragments by semantically equivalent fragments which execute faster; in [31] 150 algebraic equivalence rules have been developed, of which 40 are used in the rasdaman system for achieving a canonical query representation and 110 are optimizing. Parallel request processing in distributed environments has been implemented and tested in a Beowulf cluster [15]. Transposing OLAP preaggregation to imagery for fast multi-dimensional scaling and summarization is among our ongoing research [14].…”

Section: Discussionmentioning

confidence: 99%

The OGC web coverage processing service (WCPS) standard

Baumann

2009

Geoinformatica

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104

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Imagery is more and more becoming integral part of geo services. More generally, an increasing variety of sensors is generating massive amounts of data whose quantized nature frequently leads to rasterized data structures. Examples include 1-D time series, 2-D imagery, 3-D image time series and x/y/z spatial cubes, and 4-D x/y/z/t spatio-temporal cubes. The massive proliferation of such raster data through a rapidly growing number of services make open, standardized service interfaces increasingly important. Geo service standardization is undertaken by the Open GeoSpatial Consortium (OGC). The core raster service standard is the Web Coverage Service (WCS) which specifies retrieval based on subsetting, scaling, and reprojection. In 2008, OGC has issued a companion standard which adds flexible, open-ended coverage processing capabilities. This Web Coverage Processing Service (WCPS) specifies a coverage processing language allowing clients to send requests of arbitrary complexity for evaluation by the server. This contribution reports on the WCPS standard by giving an introduction to its coverage model and processing language. Further, design rationales are discussed, as well as background and relation to other OGC standards. 1-D to 4-D use case scenarios illustrate intended use and benefits for different communities. Although the paper focuses on conceptual issues, the WCPS reference implementation, PetaScope, is briefly addressed. The author is co-chair of the coverage-related working groups in OGC.

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Section: Discussionmentioning

confidence: 99%

The OGC web coverage processing service (WCPS) standard

Baumann

2009

Geoinformatica

Self Cite

104

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“…In the context of big data analysis and geospatial data management the improvement of data-driven workflows has been extensively discussed (Laney, 2001;Chen et al, 2014;Cheng et al, 2014;Lee and Kang, 2015;Breunig et al, 2016;Li et al, 2016;Werner and Chiang, 2021). In particular, parallel query support (Hahn et al, 2002) based on parallel hardware and software architectures (Xiaoqiang and Yuejin, 2010;Taylor, 2010;Lenka et al, 2017;SpatialHadoop, 2023) has been investigated. Intensive research has also been carried out in the field of raster databases focusing on the efficient storage of raster data (Baumann et al, 1997) and services (Baumann, 2010) to improve the access on raster data and operations (Zhong et al, 2011;Ouyang et al, 2013;Hu et al, 2018).…”

Section: Related Workmentioning

confidence: 99%

Improving Data Quality and Management for Remote Sensing Analysis: Use-Cases and Emerging Research Questions

Breunig,

Kuper,

Reitze

et al. 2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. During the last decades satellite remote sensing has become an emerging technology producing big data for various application fields every day. However, data quality checking as well as the long-time management of data and models are still issues to be improved. They are indispensable to guarantee smooth data integration and the reproducibility of data analysis such as carried out by machine learning models. In this paper we clarify the emerging need of improving data quality and the management of data and models in a geospatial database management system before and during data analysis. In different use cases various processes of data preparation and quality checking, integration of data across different scales and references systems, efficient data and model management, and advanced data analysis are presented in detail. Motivated by these use cases we then discuss emerging research questions concerning data preparation and data quality checking, data management, model management and data integration. Finally conclusions drawn from the paper are presented and an outlook on future research work is given.

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“…In the context of big data analysis as well as 3D geo-information science the improvement of data preparation and analysis for spatio-temporal data has been extensively discussed (Breunig and Zlatanova, 2011;Chen et al, 2014;Lee and Kang, 2015;Laney, 2001;Liu et al, 2009;Li et al, 2016;Mazroob et al, 2018). In particular, parallel query support (Hahn et al, 2002) based on parallel hardware and software architectures (Xiaoqiang and Yuejin, 2010;Sugumaran et al, 2012;Lenka et al, 2017; IBM big data and analytics hub, 2019; SpatialHadoop, 2019) has been investigated. Intensive research has also been carried out in the field of raster databases focusing on the efficient storage of raster data (Baumann et al, 1997) and services to improve the access on raster data for applications in the geosciences (Zhong et al, 2011;Ouyang et al, 2013;Hu et al, 2018).…”

Section: Related Workmentioning

confidence: 99%

Towards Intelligent Geo-Database Support for Earth System Observation: Improving the Preparation and Analysis of Big Spatio-Temporal Raster Data

Semnani

Breunig

Al-Doori³

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The European COPERNICUS program provides an unprecedented breakthrough in the broad use and application of satellite remote sensing data. Maintained on a sustainable basis, the COPERNICUS system is operated on a free-and-open data policy. Its guaranteed availability in the long term attracts a broader community to remote sensing applications. In general, the increasing amount of satellite remote sensing data opens the door to the diverse and advanced analysis of this data for earth system science.However, the preparation of the data for dedicated processing is still inefficient as it requires time-consuming operator interaction based on advanced technical skills. Thus, the involved scientists have to spend significant parts of the available project budget rather on data preparation than on science. In addition, the analysis of the rich content of the remote sensing data requires new concepts for better extraction of promising structures and signals as an effective basis for further analysis.In this paper we propose approaches to improve the preparation of satellite remote sensing data by a geo-database. Thus the time needed and the errors possibly introduced by human interaction are minimized. In addition, it is recommended to improve data quality and the analysis of the data by incorporating Artificial Intelligence methods. A use case for data preparation and analysis is presented for earth surface deformation analysis in the Upper Rhine Valley, Germany, based on Persistent Scatterer Interferometric Synthetic Aperture Radar data. Finally, we give an outlook on our future research.

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Parallel Query Support for Multidimensional Data: Inter-object Parallelism

Cited by 10 publications

References 4 publications

The OGC web coverage processing service (WCPS) standard

The OGC web coverage processing service (WCPS) standard

Improving Data Quality and Management for Remote Sensing Analysis: Use-Cases and Emerging Research Questions

Towards Intelligent Geo-Database Support for Earth System Observation: Improving the Preparation and Analysis of Big Spatio-Temporal Raster Data

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