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Title: Designing the Cloud-based DOE Systems Biology Knowledgebase

Abstract

Systems Biology research, even more than many other scientific domains, is becoming increasingly data-intensive. Not only have advances in experimental and computational technologies lead to an exponential increase in scientific data volumes and their complexity, but increasingly such databases themselves are providing the basis for new scientific discoveries. To engage effectively with these community resources, integrated analyses, synthesis and simulation software is needed, regularly supported by scientific workflows. In order to provide a more collaborative, community driven research environment for this heterogeneous setting, the Department of Energy (DOE) has decided to develop a federated, cloud based cyber infrastructure - the Systems Biology Knowledgebase (Kbase). Pacific Northwest National Laboratory (PNNL) with its long tradition in data intensive science lead two of the five initial pilot projects, these two focusing on defining and testing the basic federated cloud-based system architecture and develop a prototype implementation. Hereby the community wide accessibility of biological data and the capability to integrate and analyze this data within its changing research context were seen as key technical functionalities the Kbase needed to enable. In this paper we describe the results of our investigations into the design of a cloud based federated infrastructure for: (1) Semantics driven datamore » discovery, access and integration; (2) Data annotation, publication and sharing; (3) Workflow enabled data analysis; and (4) Project based collaborative working. We describe our approach, exemplary use cases and our prototype implementation that demonstrates the feasibility of this approach.« less

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1028554
Report Number(s):
PNNL-SA-77086
TRN: US201122%%395
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW 2011) , 1062 - 1071, Anchorage (Alaska), 16-20 May 2011
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; COMPUTER ARCHITECTURE; BIOLOGY; CLOUDS; DATA ANALYSIS; DESIGN; FOCUSING; IMPLEMENTATION; PROCESSING; SIMULATION; SYNTHESIS; TESTING; PARALLEL PROCESSING; workflow, semantic technologies; linked data; systems biology; cloud computing, data cloud; federated architecture

Citation Formats

Lansing, Carina S., Liu, Yan, Yin, Jian, Corrigan, Abigail L., Guillen, Zoe C., Kleese van Dam, Kerstin, and Gorton, Ian. Designing the Cloud-based DOE Systems Biology Knowledgebase. United States: N. p., 2011. Web. doi:10.1109/IPDPS.2011.261.
Lansing, Carina S., Liu, Yan, Yin, Jian, Corrigan, Abigail L., Guillen, Zoe C., Kleese van Dam, Kerstin, & Gorton, Ian. Designing the Cloud-based DOE Systems Biology Knowledgebase. United States. doi:10.1109/IPDPS.2011.261.
Lansing, Carina S., Liu, Yan, Yin, Jian, Corrigan, Abigail L., Guillen, Zoe C., Kleese van Dam, Kerstin, and Gorton, Ian. Thu . "Designing the Cloud-based DOE Systems Biology Knowledgebase". United States. doi:10.1109/IPDPS.2011.261.
@article{osti_1028554,
title = {Designing the Cloud-based DOE Systems Biology Knowledgebase},
author = {Lansing, Carina S. and Liu, Yan and Yin, Jian and Corrigan, Abigail L. and Guillen, Zoe C. and Kleese van Dam, Kerstin and Gorton, Ian},
abstractNote = {Systems Biology research, even more than many other scientific domains, is becoming increasingly data-intensive. Not only have advances in experimental and computational technologies lead to an exponential increase in scientific data volumes and their complexity, but increasingly such databases themselves are providing the basis for new scientific discoveries. To engage effectively with these community resources, integrated analyses, synthesis and simulation software is needed, regularly supported by scientific workflows. In order to provide a more collaborative, community driven research environment for this heterogeneous setting, the Department of Energy (DOE) has decided to develop a federated, cloud based cyber infrastructure - the Systems Biology Knowledgebase (Kbase). Pacific Northwest National Laboratory (PNNL) with its long tradition in data intensive science lead two of the five initial pilot projects, these two focusing on defining and testing the basic federated cloud-based system architecture and develop a prototype implementation. Hereby the community wide accessibility of biological data and the capability to integrate and analyze this data within its changing research context were seen as key technical functionalities the Kbase needed to enable. In this paper we describe the results of our investigations into the design of a cloud based federated infrastructure for: (1) Semantics driven data discovery, access and integration; (2) Data annotation, publication and sharing; (3) Workflow enabled data analysis; and (4) Project based collaborative working. We describe our approach, exemplary use cases and our prototype implementation that demonstrates the feasibility of this approach.},
doi = {10.1109/IPDPS.2011.261},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2011},
month = {9}
}

Conference:
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