DataVault: A Data Storage Infrastructure for the Einstein Toolkit
Yufeng Luo, Roland Haas, Qian Zhang, Gabrielle Allen
TL;DR
DataVault is a new data storage infrastructure designed to facilitate data sharing, search, and analysis in numerical simulations research, with detailed architecture, use cases, and future development plans.
Contribution
This paper introduces DataVault, a novel data repository tailored for the Einstein Toolkit community, including its architecture, deployment, and use-case scenarios.
Findings
Analyzed critical features of existing repositories
Demonstrated DataVault's architecture and workflows
Outlined future development directions
Abstract
Data sharing is essential in the numerical simulations research. We introduce a data repository, DataVault, that is designed for data sharing, search and analysis. A comparative study of existing repositories is performed to analyze features that are critical to a data repository. We describe the architecture, workflow, and deployment of DataVault, and provide three use-case scenarios for different communities to facilitate the use and application of DataVault. Potential features are proposed and we outline the future development for these features.
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