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Repository librarians can now efficiently mint Digital Object Identifiers (DOIs) on demand using a custom Python script, improving research discoverability and data accuracy. This automation streamlines the process for diverse digital repository content.

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Area of Science:

  • Library and Information Science
  • Digital Curation
  • Scholarly Communication

Background:

  • Digital Object Identifiers (DOIs) are crucial for persistent identification and citation of research outputs.
  • Manual DOI minting is time-consuming for repository librarians, especially with mixed content types.
  • Existing bulk DOI minting solutions may not suit repositories with unique item requirements.

Purpose of the Study:

  • To develop an automated, on-demand DOI minting solution for an institutional repository.
  • To address the challenge of minting DOIs for diverse original materials alongside pre-existing publications.
  • To enhance the efficiency and accuracy of the DOI minting workflow.

Main Methods:

  • A paired programming approach was used to develop a Python script for automated DOI minting.
  • The script leverages Application Programming Interfaces (APIs) from DataCite and the Open Repository platform.
  • Weekly one-hour sessions focused on development, testing, metadata integration, and data cleaning.

Main Results:

  • A functional Python script was created to mint DOIs on demand for individual repository items.
  • The script enhances metadata quality within DataCite and improves the overall accuracy of DOI assignments.
  • The DOI minting process has become significantly more efficient for repository staff.

Conclusions:

  • Custom scripting offers an effective solution for automating DOI minting in institutional repositories.
  • Collaborative development, combining library and technical expertise, fosters skill enhancement and successful tool creation.
  • Future development aims to further integrate DOI minting with repository metadata updates.