PATHWAY TO AI READINESS

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Data Quality

Vision

High-quality data that accurately represents mission tasks, enabling on-demand analytics and AI development, while ensuring long-term sustainment.

Essential Self-Assessment Questions

  • Are our data formats consistent with the modern requirements for AI-enabled applications?
  • Are our data formats standardized across systems, or are they machine-readable and easily convertible where necessary?
  • Do we have labeled and/or representative data that is accessible for continuous AI training and development?
  • How complete is our data for its intended use, and are there any significant gaps that could affect AI outcomes?
  • What processes do we have in place to regularly evaluate and ensure the accuracy of our data?

Resources and Links

Federated Data Catalog - Minimum Metadata Requirements

Provides details on DoD's federation model and approach to data cataloging in enabling Components to develop their catalogs to support local requirements and increase visibility.

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DoD Metadata Guidance

Guidance that consolidates and clarifies existing policy and requirements from a variety of DoD and Federal sources.

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Guidance on Designating Authoritative Data Sets

Provides interim guidance on the designation of an Authoritative Data Set (ADS).

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DoD Data Stewardship Guidebook

Amplifies and extends key concepts from the DoD Data Strategy.

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NIST Research Data Framework (RDaF)

Provides a multifaceted and customizable tool that aims to help shape the future of open data access and research data management (RDM).

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