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Related Experiment Video

Updated: Apr 5, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Standards-based metadata procedures for retrieving data for display or mining utilizing persistent (data-DOI)

Matthew J Harvey1, Nicholas J Mason2, Andrew McLean1

  • 1High Performance Computing Service, Imperial College London, London, UK.

Journal of Cheminformatics
|August 11, 2015
PubMed
Summary
This summary is machine-generated.

New metadata standards enable automated scientific data retrieval from digital repositories. This improves data access and discoverability for researchers using persistent identifiers and data attributes.

Keywords:
DOIData retrievalDigital repositoryMetadata standards

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Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Data science

Background:

  • Scientific data is often stored in digital repositories.
  • Accessing and retrieving this data can be challenging.
  • Current methods for data retrieval lack standardization.

Purpose of the Study:

  • To develop and demonstrate procedures for automated scientific data retrieval.
  • To improve the accessibility and discoverability of data in digital repositories.
  • To leverage metadata standards for enhanced data management.

Main Methods:

  • Developed three procedures based on metadata standards.
  • Utilized persistent identifiers for dataset retrieval.
  • Incorporated optional data document attributes (e.g., filename, media type).
  • Demonstrated procedures using JSmol and Avogadro.

Main Results:

  • Successfully demonstrated automated data retrieval using metadata standards.
  • Compared proposed methods with existing data retrieval practices.
  • Showcased the effectiveness of standards-based metadata for data access.

Conclusions:

  • Adopting a standards-based approach is crucial for data repositories.
  • Metadata declarations significantly enhance data accessibility.
  • The proposed methods increase the discoverability of repository-based scientific data.