Individual DOI minting for Open Repository: a script for creating a DOI on demand for a DSpace repository
Digital Object Identifiers (DOIs) are a key persistent identifier in the publishing landscape to ensure the discoverability and citation of research products. Minting DOIs can be a time-consuming task for repository librarians. This process can be automated since the metadata for DOIs is already in...
Uloženo v:
| Vydáno v: | Journal of the Medical Library Association Ročník 113; číslo 1; s. 86 - 87 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
Medical Library Association
01.01.2025
University Library System, University of Pittsburgh |
| Témata: | |
| ISSN: | 1536-5050, 1558-9439, 1558-9439 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Shrnutí: | Digital Object Identifiers (DOIs) are a key persistent identifier in the publishing landscape to ensure the discoverability and citation of research products. Minting DOIs can be a time-consuming task for repository librarians. This process can be automated since the metadata for DOIs is already in the repository record and DataCite, a DOI minting organization, and Open Repository, a DSpace repository platform, both have application programming interfaces (APIs). Existing software enables bulk DOI minting. However, the institutional repository at UMass Chan Medical School contains a mixture of original materials that need DOIs (dissertations, reports, data, etc.) and previously published materials that already have DOIs such as journal articles.
An institutional repository librarian and her librarian colleague with Python experience embarked on a paired programming project to create a script to mint DOIs on demand in DataCite for individual items in the institution’s Open Repository instance. The pair met for one hour each week to develop and test the script using combined skills in institutional repositories, metadata, DOI minting, coding in Python, APIs, and data cleaning. The project was a great learning opportunity for both librarians to improve their Python coding skills. The new script makes the DOI minting process more efficient, enhances metadata in DataCite, and improves accuracy. Future script enhancements such as automatically updating repository metadata with the new DOI are planned after the repository upgrade to DSpace 7. |
|---|---|
| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1536-5050 1558-9439 1558-9439 |
| DOI: | 10.5195/jmla.2025.2076 |