Data Notes - Wellcome Open Research - F1000 Research

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Data Notes

Short peer reviewed articles that describe why and how a dataset was created. Publish your Data Notes on Wellcome Open Research to maximize the potential of your research data.

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Effective data sharing extends beyond simply depositing your dataset in a repository. At Wellcome Open Research, we believe that data should be shared in a discoverable, useable and reproducible way. Enter: Data Notes.

Data Notes are an article type offered on Wellcome Open Research which allow researchers to describe their scientific dataset, including:

  • Dataset rationale, protocol, and validation details
  • Information about any limitations of the dataset
  • Information on where and how to access the dataset, as part of a Data Availability Statement
  • Reference to the dataset using a formal data citation

Data Notes do not include any analyses or conclusions, but promote the discoverability and potential reuse of research data by providing a detailed description of the dataset itself. This gives credit to data producers with a citable, peer-reviewed publication, and supports new research collaborations across disciplines.

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Instructions for authors

Ready to submit? Following these simple guidelines will ensure you’ve prepared your Data Note correctly.
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What does a Data Note look like?

A key benefit to publishing a Data Note article is the potential for your dataset to be reused, supporting further research and making an impact across disciplines.

Below are two great examples of this in action:  

The genome sequence of the Eurasian river otter

Read the article

A validation series for benchmarking cancer predisposition genes

Read the article

What are the benefits of publishing a Data Note on Wellcome Open Research?

Maximize the potential of your research data

Data Notes let you share contextual information about your scientific datasets in a highly discoverable, useable and reproducible way. This maximizes the potential reach and reuse of your data, and can even support inter-disciplinary research collaborations in the future. Like all content published on Welcome Open Research, Data Notes are fully open access, meaning your article is easily available to all stakeholders, including fellow researchers, NGOs, and policymakers.

Credit where it’s due

Data Notes are a peer-reviewed, fully citable publication with a DOI, offering recognition and credit to data producers, which isn’t always possible within more traditional publishing formats. Data Notes do not undermine the novelty or value of a Research Article which makes use of the published dataset. In fact, Data Notes work best when they can be linked to a traditional Research Article reporting analysis of the published dataset, along with the results and conclusions; and there’s some evidence that linking your publications to your research data could increase the citation potential of your work. 

Get help with data management

Wellcome Open Research offer editorial support in making source data openly available, including expert guidance on preparing your data and choosing an appropriate repository for your work. Data Notes can even support you in meeting vital requirements from your funder or institution for sharing your data appropriately, so that others can access and reuse your datasets.

Increase the discoverability of your research

Once your Data Note has passed peer review, inclusion in Scopus, PubMed, Google Scholar and other major indexers will help it reach more readers. Furthermore, Data Notes include validated links to the dataset in your chosen repository, and your article is supported by machine-readable metadata to support greater discoverability.

All types of data welcome

We understand that data can come in many forms. Whether your dataset is computational, experimental, observational, curated (or something else entirely) we welcome your Data Note article on Wellcome Open Research.

How to write a Data Note

Download our free guide for authors on how to write a Data Note for submission to Wellcome Open Research. This template walks through every section of this unique article type, explaining what details need to be included to make your Data Note as useful as possible for future researchers.

This guide for researchers is available in two formats:

  • A PDF, ideal for reading and referencing even when you’re on the move
  • A fully editable Word document, so you can work on your Data Note directly within the template

Download the PDF        Download the Word Document 

Open data on Wellcome Open Research | Policies and principles

Wellcome Open Research advocates an Open Data Policy. Others need access to the original, raw data to be able to replicate a given study, reproduce the original findings, or reuse the data to support their own research. Therefore, all articles on the Wellcome Open Research platform should include citations to repositories that host the data underlying the results, together with details of the software tools used to process these. Of course, there may be exceptional cases where openly sharing research data is not feasible – for example, due to ethical, data protection, or confidentiality reasons. You can find out more in our Data Guidelines.

Alongside our Open Data policy, Wellcome Open Research endorses the FAIR Data Principles which aim to make research data Findable, Accessible, Interoperable, and Reusable; together these provide a framework to promote the broadest possible reuse of scientific data.

Read our guide to making your data FAIR

Need help getting started with data sharing?

Repositories

Choosing the right repository for your research can be daunting. This handy guide asks you three simple questions to help determine the best repository for you.
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Spreadsheets

Stuck on how to keep your spreadsheets interoperable and reusable? We’ve put together some do’s and don’ts to ensure your spreadsheets follow best practice.
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Licenses

Data accessibility is defined by the presence of a user license. We’ve put together a simple rundown of the different licenses available for data and software.
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