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A Data Science Infrastructure Project

Project description

DSI User Guide

The goal of the Data Science Infrastructure Project (DSI) is to provide a flexible, AI-ready metadata query capability which returns data subject to strict, POSIX-enforced file security. The data lifecycle for AI/ML requires seamless transitions from data-intensive/AI/ML research activity to long-term archiving and shared data repositories. DSI enables flexible, data-intensive scientific workflows that meet researcher needs.

DSI is implemented in three parts:

  • Readers and Writers

  • Backends

  • Core middleware

For more information on these DSI modules, please refer to the DSI Introduction Page.

Users can interact with DSI seamlessly through two methods:

DSI Base Requirements

  • python3 (3.11 tested)

  • Cross-platform (Unix / macOS / Windows)

  • Git

  • Plugins and Backends introduce further requirements

Installation

DSI has several versioned releases and cloning from ‘main’ is the alpha-version.

Users that want to install DSI should follow our installation steps.

Release Versions

Supported release versions of DSI are tagged and found in (https://github.com/lanl/dsi/releases). Releases with minimal requirements are published on pip via (https://pypi.org/project/dsi-workflow/). To install the latest version, try the following:

python3 -m pip install dsi-workflow

Contributor Resources

DSI Contributors can view our more developer-focused documentation in the Contributor Resources.

These pages further explain DSI Readers/Writers/Backends, as well as how to write your own Reader/Writer compatible with DSI. Project contributors are encouraged to prototype solutions which do not contain sensitive data at this time.

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