Shelter from the Storm: Building a Safe Archive in a Hostile World

MacLaren, Jon; Allen, Gabrielle; Dekate, Chirag; Huang, Dayong; Hutanu, Andrei; Zhang, Chongjie

doi:10.1007/11575863_49

Cited by 14 publications

(11 citation statements)

References 7 publications

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“…The SURA Coastal Ocean Observing and Prediction (SCOOP) program is building a modeling and observation cyberinfrastructure to provide new enabling tools for a virtual community of coastal researchers. Two goals of the project are to enable effective and rapid fusion of observed oceanographic data with numerical models and to facilitate the rapid dissemination of information to operational, scientific, and public or private users (MacLaren et al, 2005). As part of the SCOOP program, the team at LSU has built an archive to store simulation and observational data sets.…”

Section: Guiding Application Scenariosmentioning

confidence: 99%

Semantic enabled metadata management in PetaShare

Wang

Huang

Akturk

et al. 2009

IJGUC

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We designed a semantic enabled metadata framework using ontology for multi-disciplinary and multi-institutional large scale scientific data sets in a Data Grid setting. Two main issues are addressed: data integration for semantically and physically heterogeneous distributed knowledge stores, and semantic reasoning for data verification and inference in such a setting. This framework enables data interoperability between otherwise semantically incompatible data sources, cross-domain query capabilities and multi-source knowledge extraction. In this paper, we present the basic system architecture for this framework, as well as an initial implementation. We also analyze a real-life scenario and show integration of our framework into the PetaShare Data Grid where multi-disciplinary data archives are geographically distributed across six research institutions in Louisiana.

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Section: Guiding Application Scenariosmentioning

confidence: 99%

Semantic enabled metadata management in PetaShare

Wang

Huang

Akturk

et al. 2009

IJGUC

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“…Here, severe storm events initiate automated model workflows triggered by National Hurricane Center advisories, high resolution wind fields are generated which then initiate ensembles of hydrodynamic models. The resulting data fields are distributed to the SCOOP partners for visualization and analysis, and are placed in a highly available archive [2].…”

Section: Sura Coastal Ocean Observing and Prediction (Scoop)mentioning

confidence: 99%

“…-Data Management. Through the SCOOP project a highly reliable coastal data archive [2] has been implemented at LSU, with 7TB of local storage and 7TB of remote storage (SDSC SRB) for historical data. This archive was designed to ingest and provide model (surge, wave, wind) and observational (sensor, satellite) data, and is integrated with a SCOOP catalogue service at UAH.…”

Section: Dynacode Componentsmentioning

confidence: 99%

“…The system is designed to support rapid experimentation rather than complex workflows, and provides a completely data-driven architecture with the ensemble runs being triggered by the arrival of input wind files. As ensemble runs complete, results are fed to a visualization service and also archived in the ROAR Archive [2]. Metadata relating to the run and the result set is fed into the catalog developed at UAH via a service interface.…”

Section: Dynacode Componentsmentioning

confidence: 99%

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Building a Dynamic Data Driven Application System for Hurricane Forecasting

Allen

2007

Computational Science – ICCS 2007

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Abstract. The Louisiana Coastal Area presents an array of rich and urgent scientific problems that require new computational approaches. These problems are interconnected with common components: hurricane activity is aggravated by ongoing wetland erosion; water circulation models are used in hurricane forecasts, ecological planning and emergency response; environmental sensors provide information for models of different processes with varying spatial and time scales. This has prompted programs to build an integrated, comprehensive, computational framework for meteorological, coastal, and ecological models. Dynamic and adaptive capabilities are crucially important for such a framework, providing the ability to integrate coupled models with real-time sensor information, or to enable deadline based scenarios and emergency decision control systems. This paper describes the ongoing development of a Dynamic Data Driven Application System for coastal and environmental applications (DynaCode), highlighting the challenges of providing accurate and timely forecasts for hurricane events.

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“…The resulting data fields obtained from both the operational and storm event scenarios are distributed to the SCOOP partners for local visualization and further analysis, and are also archived for further use in a high available archive [15]. …”

Section: Sura Coastal Ocean Observing and Predictionmentioning

confidence: 99%

Designing a Dynamic Data Driven Application System for Coastal and Environmental Modeling

Allen

Bogden

Luettich

et al. 2007

IFIP the International Federation for Information Processing

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The economically important Louisiana Coastal Area (LCA) is susceptible to hurricane activity which is increasingly aggravated by the continuing erosion of wetlands. Various programs are aimed at building sophisticated models of meteorological, coastal, and ecological processes. The emerging paradigm of Dynamic Data Driven Application Systems (DDDAS) can be applied to these models leading to new scenarios for integrated, real-time simulations that include feedback control with sensors and simulations. This paper describes the motivation and components for a comprehensive DDDAS for coastal and environmental modeling and the implications this has for scientific libraries and high performance computing.

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Shelter from the Storm: Building a Safe Archive in a Hostile World

Cited by 14 publications

References 7 publications

Semantic enabled metadata management in PetaShare

Semantic enabled metadata management in PetaShare

Building a Dynamic Data Driven Application System for Hurricane Forecasting

Designing a Dynamic Data Driven Application System for Coastal and Environmental Modeling

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