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Related Experiment Video

Updated: Nov 29, 2025

Dendrochronological Dating and Provenancing of String Instruments
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The End-to-End Provenance Project.

Aaron M Ellison1, Emery R Boose1, Barbara S Lerner2

  • 1Harvard University, Harvard Forest, 324 North Main Street, Petersham, MA 01366, USA.

Patterns (New York, N.Y.)
|November 18, 2020
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Summary
This summary is machine-generated.

Data provenance provides a traceable history for datasets, crucial for reproducing analyses and validating scientific findings. Professionals developed software tools to manage this essential data history.

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Area of Science:

  • Computer Science
  • Data Science
  • Scientific Computing

Background:

  • Data provenance is a machine-readable record detailing a dataset's origin and processing.
  • It enhances dataset value by ensuring transparency and reproducibility.
  • Understanding data provenance is vital for scientific integrity and validation.

Discussion:

  • The End-to-End Provenance Project community focuses on creating practical software solutions.
  • These tools facilitate the collection and utilization of comprehensive data provenance information.
  • Effective provenance management supports robust scientific workflows.

Key Insights:

  • Machine-readable data provenance summaries are essential for scientific reproducibility.
  • Provenance tracking validates computational analyses and scientific conclusions.
  • Community-driven software development accelerates provenance adoption.

Outlook:

  • Future work will likely involve more sophisticated provenance tracking and analysis tools.
  • Integrating provenance into standard research practices will increase scientific rigor.
  • The End-to-End Provenance Project aims to foster wider adoption of provenance standards.