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Title: Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015

Abstract

The Environmental System Science (ESS) activity within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) seeks to advance a robust, predictive understanding of terrestrial environments, extending from bedrock to the top of the vegetative canopy and from molecular to global scales, through an iterative cycle of model-driven experimentation and observation dubbed MODEX. Considerable progress has been made toward achieving this overarching goal, but widely recognized is the fragmentation across projects and disciplines of the relevant modeling and simulation capabilities, observational and experimental data, analysis algorithms, and workflow tools. This fragmentation creates significant challenges for studying impacts and feedbacks in these complex multiscale systems. These challenges are further exacerbated by ongoing disruptive changes in high-performance computational architectures and the exponential growth in the types and volume of data that render obsolete the conventional approaches to software development and data management. Overcoming these challenges will require the development of a BER Climate and Environmental Sciences Division (CESD)–wide enabling cyberinfrastructure to support data management, cross-domain modeling, data analysis, and collaborative research. To explore the potential for working groups to initiate and guide a more integrated and community-based cyberinfrastructure, BER held the ESS Workshop on Model-Data Integration: Modeling Frameworks, Datamore » Management, and Scientific Workflows on April 30-May 1, 2015, following the ESS Principal Investigator Meeting in Potomac, Maryland. Participants included model developers, software engineers, and data management specialists from eight national laboratories, which represented a wide range of projects and programs from CESD as well as cross-cutting projects from DOE’s Office of Advanced Scientific Computing Research (ASCR; both BER and ASCR are operated from within DOE’s Office of Science). A series of plenary talks provided background information and clarified the workshop’s three objectives: (1) develop requirements for this community-based cyberinfrastructure to ensure enhanced scientific productivity of the community as a whole; (2) identify challenges associated with developing this new cyberinfrastructure using a phased approach guided by project-driven use cases; and, given these requirements and challenges, (3) chart a path forward for ESS working groups to lead the phased development of the new cyberinfrastructure.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [3];  [6];  [3];  [4];  [3];  [4]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  5. Subsurface Insights, Inc., Hanover, NH (United States)
  6. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
USDOE Office of Science (SC), Washington, D.C. (United States). Biological and Environmental Research (BER)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1471414
Report Number(s):
DOE/SC-0178
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 54 ENVIRONMENTAL SCIENCES

Citation Formats

Moulton, David, Williams, Dean, Agarwal, Deb, Boden, Tom, Versteeg, Roelof, Koven, Charlie, Scheibe, Tim, Steefel, Carl, Thornton, Peter, Wainwright, Haruko, and Painter, Scott. Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015. United States: N. p., 2015. Web. doi:10.2172/1471414.
Moulton, David, Williams, Dean, Agarwal, Deb, Boden, Tom, Versteeg, Roelof, Koven, Charlie, Scheibe, Tim, Steefel, Carl, Thornton, Peter, Wainwright, Haruko, & Painter, Scott. Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015. United States. https://doi.org/10.2172/1471414
Moulton, David, Williams, Dean, Agarwal, Deb, Boden, Tom, Versteeg, Roelof, Koven, Charlie, Scheibe, Tim, Steefel, Carl, Thornton, Peter, Wainwright, Haruko, and Painter, Scott. Mon . "Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015". United States. https://doi.org/10.2172/1471414. https://www.osti.gov/servlets/purl/1471414.
@article{osti_1471414,
title = {Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015},
author = {Moulton, David and Williams, Dean and Agarwal, Deb and Boden, Tom and Versteeg, Roelof and Koven, Charlie and Scheibe, Tim and Steefel, Carl and Thornton, Peter and Wainwright, Haruko and Painter, Scott},
abstractNote = {The Environmental System Science (ESS) activity within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) seeks to advance a robust, predictive understanding of terrestrial environments, extending from bedrock to the top of the vegetative canopy and from molecular to global scales, through an iterative cycle of model-driven experimentation and observation dubbed MODEX. Considerable progress has been made toward achieving this overarching goal, but widely recognized is the fragmentation across projects and disciplines of the relevant modeling and simulation capabilities, observational and experimental data, analysis algorithms, and workflow tools. This fragmentation creates significant challenges for studying impacts and feedbacks in these complex multiscale systems. These challenges are further exacerbated by ongoing disruptive changes in high-performance computational architectures and the exponential growth in the types and volume of data that render obsolete the conventional approaches to software development and data management. Overcoming these challenges will require the development of a BER Climate and Environmental Sciences Division (CESD)–wide enabling cyberinfrastructure to support data management, cross-domain modeling, data analysis, and collaborative research. To explore the potential for working groups to initiate and guide a more integrated and community-based cyberinfrastructure, BER held the ESS Workshop on Model-Data Integration: Modeling Frameworks, Data Management, and Scientific Workflows on April 30-May 1, 2015, following the ESS Principal Investigator Meeting in Potomac, Maryland. Participants included model developers, software engineers, and data management specialists from eight national laboratories, which represented a wide range of projects and programs from CESD as well as cross-cutting projects from DOE’s Office of Advanced Scientific Computing Research (ASCR; both BER and ASCR are operated from within DOE’s Office of Science). A series of plenary talks provided background information and clarified the workshop’s three objectives: (1) develop requirements for this community-based cyberinfrastructure to ensure enhanced scientific productivity of the community as a whole; (2) identify challenges associated with developing this new cyberinfrastructure using a phased approach guided by project-driven use cases; and, given these requirements and challenges, (3) chart a path forward for ESS working groups to lead the phased development of the new cyberinfrastructure.},
doi = {10.2172/1471414},
url = {https://www.osti.gov/biblio/1471414}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {11}
}