About the Data Journals Dashboard

Last update: 2026-06-02

Contents

Introduction

The Data Journals Dashboard provides access to a collection of data journals first published by Maxi Kindling & Dorothea Strecker in 2022 [Zenodo]. With additional metadata from the Directory of Open Access Journals the dashboard enables researchers, research data management (RDM) professionals, librarians and all other interested parties to search and filter the collection and select a data journal that meets their publication needs.

The Data Journals Dashboard is maintained by the Research Data Center of the University Library Mannheim.

What are Data Journals?

Data journals are scientific journals that primarily or to a large extend publish data papers, data reports, and similar article types. These articles describe datasets produced through research activities, but do not interpret the results. Instead, data journals focus on providing detailed documentation of how, when and with which methodology datasets were created, where they are accessible, and how they can be reused by others. As most data journals are peer-reviewed, data papers promote good research and RDM practices; they also benefit researchers who create and share high-quality datasets, as they follow established scientific communication practices and receive citations.

Journal Metadata

Primary Dataset

The dashboard’s primary data source are data journal metadata published under CC0 1.0 Universal on Zenodo and Github:

Augmented Dataset

The primary dataset is enhanced by adding additional metadata via the Directory of Open Access Journals API. Each ISSN in the primary dataset is queried via the API. If the ISSN is present in the DOAJ, additional metadata is retrieved and added to the journal’s existing metadata. The full metadata schema used to integrate both data sources is available on GitHub.

For ISSNs not present in the DOAJ manual metadata augmentations are made using the journal’s website, ISSN Portal, Wikidata and other sources. Each data journal page provides a list of the specific sources used for metadata augmentation.

Dataset Dump

The augmented dataset containing all metadata can be dowloaded as CSV, YAML and JSON on Github.

Licenses

  • The primary dataset by Kindling & Strecker (2022) is licensed under CC0 1.0 Universal [Source]
  • Metadata retrieved via the Directory of Open Access Journals API is licensed under CC0 1.0 Universal [Source]
  • The augmented dataset (DJD metadata collection) is licensed under CC0 1.0 Universal [CC0 1.0 deed]
  • The DJD metadata schema of the Data Journals Dashboard is licensed under CC0 1.0 Universal [CC0 1.0 deed]

Contributions

Contribute to the Data Journals Dashboard by suggesting a new data journal via a GitHub issue using the “Add Data Journal” template. The template will ask for the journal’s ISSN, title, publisher, URL, data_journal_type, and status. After submitting the issue, a maintainer will review your contribution. Once approved, the new journal will be processed and added to the collection.

Use of AI

Claude Code (Sonnet 4.6) was used for coding, bug fixing and testing the Python data processing pipeline as well as the Hugo app.

Additional journal metadata not provided by the Directory of Open Access Journals’ API was for a large part collected with Claude Code and its web search tool, and then manually verified and cleaned.

Citing the Dashboard

If you use the Data Journals Dashboard in your research or work, please cite it as follows: