Server-side workflow execution using data grid technology for reproducible analyses of data-intensive hydrologic systems

11Citations
Citations of this article
30Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Many geoscience disciplines utilize complex computational models for advancing understanding and sustainable management of Earth systems. Executing such models and their associated data preprocessing and postprocessing routines can be challenging for a number of reasons including (1) accessing and preprocessing the large volume and variety of data required by the model, (2) postprocessing large data collections generated by the model, and (3) orchestrating data processing tools, each with unique software dependencies, into workflows that can be easily reproduced and reused. To address these challenges, the work reported in this paper leverages the Workflow Structured Object functionality of the Integrated Rule-Oriented Data System and demonstrates how it can be used to access distributed data, encapsulate hydrologic data processing as workflows, and federate with other community-driven cyberinfrastructure systems. The approach is demonstrated for a study investigating the impact of drought on populations in the Carolinas region of the United States. The analysis leverages computational modeling along with data from the Terra Populus project and data management and publication services provided by the Sustainable Environment-Actionable Data project. The work is part of a larger effort under the DataNet Federation Consortium project that aims to demonstrate data and computational interoperability across cyberinfrastructure developed independently by scientific communities.

Cite

CITATION STYLE

APA

Essawy, B. T., Goodall, J. L., Xu, H., Rajasekar, A., Myers, J. D., Kugler, T. A., … Moore, R. W. (2016). Server-side workflow execution using data grid technology for reproducible analyses of data-intensive hydrologic systems. Earth and Space Science, 3(4), 163–175. https://doi.org/10.1002/2015EA000139

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free