December 2019

Conference Paper

DataFed: Towards Reproducible Research via Federated Data Management

By:
Stansberry, Dale V; Somnath, Suhas ; Breet, Jessica U; Shutt, Gregory L; Shankar, Mallikarjun
Page Number:
1312-1317
Book Title:
2019 International Conference on Computational Science and Computational Intelligence (CSCI)
Publication Date:
December 2019
Conference Name:
THE 2019 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & COMPUTATIONAL INTELLIGENCE (CSCI)
Conference Location:
Las Vegas, Nevada, United States of America
Conference Sponsor:
IEEE
View DOI Listing:
https://doi.org/10.1109/CSCI49370.2019.00245

Abstract

The increasingly collaborative, globalized nature of scientific research combined with the need to share data and the explosion in data volumes present an urgent need for a scientific data management system (SDMS). An SDMS presents a logical and holistic view of data that greatly simplifies and empowers data organization, curation, searching, sharing, dissemination, etc. We present DataFed - a lightweight, distributed SDMS that spans a federation of storage systems within a loosely-coupled network of scientific facilities. Unlike existing SDMS offerings, DataFed uses high-performance and scalable user management and data transfer technologies that simplify deployment, maintenance, and expansion of DataFed. DataFed provides web-based and command-line interfaces to manage data and integrate with complex scientific workflows. DataFed represents a step towards reproducible scientific research by enabling reliable staging of the correct data at the desired environment.


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