Data policies and repositories
How to meet the F1000 open data policy in 5 simple steps
F1000 has a progressive open data policy in place, which requires authors to share all data underpinning their research in an open format, together with details of any software used to process the results.
It is essential that others can see the source data in order to be able to replicate the study and analyze the data, and in some circumstances, reuse it.
But, how do you make your data openly available?
Read on to uncover 5 essential steps to sharing your data openly, including:
- Identifying and preparing your data for sharing
- Depositing your data in a repository
- Applying an open license
- Writing a data availability statement
- Citing your data
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How to make your data openly available
Identify all data from the outset and prepare it for sharing
The first step is to identify your research data. Research data can take many different forms, including survey results, gene sequences, software, code, neuro-images, and even audio files. Both quantitative and qualitative data should be shared. Next, you should consider how to make your data as open as possible, and as closed as necessary. Are there any ethical or security issues around sharing your data? Do you need to anonymize your dataset to protect patient or participant privacy? Are there subject-specific data standards relevant to your research?
Deposit your research data in a data repository
A repository is a location on the web for research data to be stored and accessed by others. To enable others to find, interpret, and reproduce your research, you should deposit your research data into a repository, where you can add contextual information known as ‘metadata’ and receive a persistent identifier (DOI). Placing data in a repository helps preserve it more securely over time than hosting it on a website. An extensive list of recommended repositories is available on the ‘Data Guidelines’ page of your chosen publishing venue.
Apply an open license
All shared data should also be reusable by others. To achieve this, we require authors to apply an open license to their data. A license gives researchers a standardized way to grant others permission to use their creative work under copyright law. All datasets associated with articles submitted to F1000 publishing venues much have either a CC0 Public Domain Dedication or a CC BY Attribution Only permitting maximum reuse by others with minimal restrictions.
Write a data availability statement
A data availability statement describes all data underpinning the research and where it can be found. These statements work for any data type, including data the researcher generated, data they reused, or material from third-party sources. Even if a paper does not have any underlying data, you should still include a data availability statement to explain that you did not generate or reuse data. A data availability statement should include: the name of your chosen repository; title of the dataset; persistent identifier; description of the files; and data license.
Cite and link your dataset
Once your article is published, you need to cite your data in the body of your article and add it to your list of references using its digital object identifier (DOI). Once your research is published, some repositories allow you to add the article’s DOI to the metadata of your dataset to establish a permanent link between these two outputs of your research. Linking your data and your article in this way means they are reciprocally connected, ensuring you receive credit for your work.
Why should you share your research data?
Boost the credibility of your research
Open data enables replication and validation of your research, which in turn boosts its credibility and robustness. By sharing your data openly, your entire research project becomes more transparent.
Increase the visibility of your research
Increase the discoverability of your research by reciprocally linking your article and its related datasets. Plus, describing your data with rich, meaningful, machine-readable metadata makes it easy for humans and computers to find use.
Progress in your career
Researchers can receive increased credit and recognition by sharing their research data, which in turn may lead to increased opportunities for collaboration – even across disciplines. Additionally, one 2019 study suggests that open data can generate up to 25% more citations!
Develop a better understanding of your field
Open data supports learning and enables a deeper, richer understanding of the research topic – this is particularly useful in teaching as students can interrogate raw research data for themselves.
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