Data Notes | FAQs

What is a Data Note?

Data Notes are short descriptions of a dataset indicating why and how the data was collected. They include no analyses or conclusions but promote the discoverability and reuse of the data in line with the FAIR data principles.

How do researchers write a Data Note?

As Data Notes focus on the data and how it was produced, authors should focus on the methods and data availability statement. The methods should provide a detailed description of how the data was generated along with details of any software used to process the data. The data availability statement should provide full details of how, where, and under what conditions the data can be accessed. As part of our Open Data campaign, we have put together a useful guide on how to do this.

How much does it cost to publish a Data Note on F1000Research?

F1000Research charges an Article Processing Charge (APC) for all articles. You can find out more about these costs here.

Are Data Notes peer reviewed?

All Data Notes undergo our fully open peer review, with the reviewer’s names and reports being published alongside the article. Reviewers are asked to check that the methods have been sufficiently reported and the dataset has been published in FAIR data format.

Is it easy to publish a Data Note?

Yes! All you need is your methods and data. To make it even easier, we have a template with step by step instructions. Our editorial team are also on hand to answer any of your queries, just send an email to research@f1000.com.

How important are Data Notes within academic research?

Data sharing is hugely important to academic research, and Data Notes are a great way of facilitating open data. Data Notes can also aid discoverability through their inclusion in bibliometric databases, and so can reach more academics than a data deposit alone.

What if I can’t share my research data because it contains sensitive information? Can I still publish a Data Note?

Yes! but you should consider the following questions to ensure your data is as open as possible and as closed as necessary:

1. Can the data be de-identified sufficiently to allow the data to be shared openly?
   • We encourage authors to use the Safe Harbour method to de-identify sensitive data.
2. Can any intermediary data be shared?
   • Even when the full dataset cannot be shared intermediary data is useful to allow readers and reviewers to interpret your methods while reading your Data Note.
3. How can readers and reviewers gain access to the data?
   • We will need a route of access for readers and reviewers. Access is usually controlled by ethics boards, but we also recommend the use of controlled access repositories.

When is the best time during the research process to write and submit a Data Note?

To get the full potential out of your dataset and Data Note it’s best to publish it as soon as you have completed data collection. This way you can cite your data and Data Note in any articles where you use your dataset.

I have a question which isn’t answered here – how do I get in touch?

Drop us an email at research@f1000.com and someone will get back to you. There's also an FAQ page on our websitewhich might answer your question. 

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