Data notes

Get more from your data set

What is a data note?

Data notes are a short peer-reviewed article type that concisely describe research data stored in a repository. They increase the discoverability and transparency of your research, helping to comply with funder mandates on data sharing and make data FAIR (findable, accessible, interoperable and reusable).

Data notes do not include any analysis or conclusions but may be linked to a research article incorporating analysis of the published dataset, as well as the results and conclusions. They may also highlight standalone data sets stored in a repository.

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What are the benefits of publishing a data note?

Publishing a data note allows you to:

  • Maximize the potential of your research data through improving the discoverability, usability, and reproducibility of your research

  • Gain appropriate credit for your research data with a citable publication

  • Reach new audiences for your research

  • Foster new collaborations across disciplines by making your data available

How do I write a data note?

Data notes must describe research data generated and owned by the authors and should include:

  1. Dataset rationale, protocol, and validation details

  2. Information about any limitations of the dataset

  3. Information on where and how to access the dataset, as part of a data availability statement

  4. Reference to the dataset using a formal citation

  5. Where applicable, cite and summarize any previous publications that use the data presented

Data note templates

Here are downloadable data note templates to help you write and prepare your data note for submission:

Publishing your data note with F1000Research

F1000Research enables you to publish your data note rapidly and openly via an author-centric platform. You’ll benefit from:

  • Open access publication – for maximum visibility of your data note.

  • Fast publication times – your data note will be published online with a DOI following our pre-publication checks in as little as 14 days.

  • Open data – All submissions to F1000Research must comply with our open data policy and support FAIR principles.

  • Open peer review – Once published, your data note will undergo a robust open peer review process where reviewers are asked specific questions about the description, methodology and availability of the data.

Please read the guide to publishing a data note with F1000Research and the data note submission template, which makes it quick and easy to write your data note for submission for F1000Research.

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Explore journals offering data notes

The Taylor & Francis journal portfolio offers a growing range of options for publishing data notes. Make sure you read the aims and scope of the journal to see if it’s the right fit for your research.

To maintain quality and provide validation of the data and supporting information, all data notes will be peer reviewed in line with the relevant submission policy.

Below are lists of journals for publishing your data notes categorized by host group: