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As a non-traditional article type, Charlie Vickers, Senior Editorial Assistant at F1000Research, discusses the benefits of publishing and reviewing a Data Note.

At F1000Research we have never been shy of innovation and a quick internet search shows that this is again the case for Data Notes, one of our many non-traditional article types. As they are uncommon in academic publishing, I thought I would take a look at what Data Notes are, and some top tips from our peer review team on how to go about reviewing them.

What is a Data Note?

A Data Note is described as a brief description of a dataset which can promote the reuse of the data, including how and why the data were created. Importantly, a Data Note will contain no analyses or conclusions, and our editorial team may advise that a submission would be more suited to another article type (such as a brief report) if an analysis or conclusion was included. Another important aspect to note is that the research data must have been produced and owned by the authors of the article. If an article has already been published which uses the data, it is important that this be cited and summarised, to avoid any problems with potential self-plagiarism.

What are the benefits of a Data Note?

The major benefit for the authors of a Data Note is that the data is then readily available to be used by others, such as for re-analysis work. This is because any article submitted to us must adhere to our Open Data policies, ensuring that the dataset is discoverable (published on a stable and recognised open repository and ideally having a DOI), usable (published under a CC0 license) and hosted in a reproducible way. An important aspect for potential submitters is that our editorial team is ready to help with any questions on our Open Data policies, and they can even help with depositing data by directing you to an appropriate repository.

Publishing a Data Note with F1000Research also means that the authors have a citable publication to showcase their data, and an easy way to share it with their colleagues. As our Data Notes all undergo peer review with the results publicly available, this also means that the data will have been independently reviewed, which is where our valued reviewers come in.

Reviewing a Data Note for F1000Research

At F1000Research, we have an open peer review model that starts when the article is published, so any changes suggested by reviewers are factored in using our version system, allowing authors to respond and revise according to the peer review reports they receive.

When reviewing for us – as part of our peer review report form – we ask reviewers a set of standard questions, with the questions and answers published as part of the peer review report. For Data Notes, we ask the following questions:

• Is the rationale for creating the dataset(s) clearly described?
• Are the protocols appropriate and is the work technically sound?
• Are sufficient details of methods and materials provided to allow replication by others?
• Are the datasets clearly presented in a useable and accessible format?

We find that our reviewers often find these very useful as they may (understandably) not have peer reviewed a Data Note (or in some cases even heard of one), with the questions offering an insight into the feedback we think should be given to the authors. In some cases, we find that reviewers will copy these questions into their reports, before expanding and explaining on their answers. More information on how to structure your peer review report can be found in this blog.

As well as this, we ask reviewers across all our article types to go into plenty of detail on their reports, as they are published along with their names and affiliation. Not only does this give reviewers the opportunity to offer suggestions for improvements to the article, but we also encourage any strengths to be pointed out as well, which readers of the article and the respective reports may find useful.

With an open peer review model, this has meant that we have developed a code of conduct for our reviewers, which offers further insight to what we expect in a peer review report. To summarise just a few of these, we ask that reports are constructive in their criticism, making sure any suggestions which are made can be implemented whilst keeping in mind the idea of reviewing as you would wish your work to be reviewed.

Benefits of reviewing a Data Note for us

We think there are many benefits to reviewing any article for F1000Resarch, not just a Data Note, owing to our open peer review model. Firstly, you receive full credit for your work, with each peer review report being assigned a digital object identifier (DOI) once it has been published. This means that your peer review report is fully citable and the number of views on your report can also be seen. A further advantage of the F1000Research model is if you review the article with a colleague, both of you will receive credit for this hard work we know our reviewers deserve.

As a final note… 

To sum up, Data Notes can only be a positive for the research community going forward, making data more accessible and reusable (for example for re-analysis). Our model at F1000Research is not only beneficial for publishing these innovative article types, but also for our reviewers who give us their valuable time and expertise, to ensure that they are thoroughly peer reviewed.