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A birth certificate for data to improve findability, accountability, and traceability.

Rongbin Li1, Avisha Das1, Yuntao Yang1

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We introduce the Data Birth Certificate, a universal framework for tracking research data from creation. This ensures data quality, provenance, and reproducibility for AI and scientific research.

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Area of Science:

  • Data Science
  • Scientific Research
  • Artificial Intelligence

Background:

  • Data quality is crucial for scientific research and AI advancement.
  • Robust traceability and accountability mechanisms are needed from data creation.
  • Existing identifiers are assigned at deposition, not at data origin.

Purpose of the Study:

  • To propose the concept of a Data Birth Certificate (DBC).
  • To establish a universal framework for identifying research data at creation.
  • To enhance data traceability, accountability, and reproducibility.

Main Methods:

  • Conceptual framework outlining the DBC.
  • Distinguishing DBC from existing identifier systems.
  • Discussing the role of DBC in data stewardship.

Main Results:

  • DBC provides immutable, origin-centered traceability.
  • Captures essential metadata at data generation (time, location, creator).
  • Complements Findability, Accessibility, Interoperability, and Reusability (FAIR) principles.

Conclusions:

  • DBC strengthens research reproducibility and data stewardship.
  • Supports reliable data tracking and accountability.
  • Enables downstream information management without constraining data reuse.