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F1000 Open Data Guidelines

Data must be in a repository

Data availability statement required

Accessible data

Data must be openly licensed

Data must be FAIR

Reusable data

Datasets must be cited

Credit for data

Peer reviewers access and assess the data as part of the peer review process

More journals implemented

More stringent policies

This is an overview of our Open Data guidelines at F1000. There are a number of elements which aim to make the data which is shared alongside published articles accessible and reusable.

To ensure that data is Accessible, we require a data availability statement explaining how data can be accessed - the must be stored in a data repository.

Reusable Data must be openly licensed and the data should ideally be shared in a way that complies with the FAIR principles, which are outlined in a later slide.

We also want the data creators to get credit for their data, so datasets should be cited in the body of the article where relevant, and added to the reference list or bibliography.

All of these requirements are checked pre-publication by our editorial team; and the datasets will be assessed by the peer reviewers as part of their evaluation of the research post-publication.

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Researchers’ attitudes and approaches

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Researchers do not go above and beyond journal policy requirements

“The citation advantage of linking publications to research data,” 2020, PLoS ONE, https://doi.org/10.1371/journal.pone.0230416

Data repository use remains low when it is not mandated by policy

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Data availability statements include minimal information, regardless of sharing approach

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Researchers do not necessarily see data sharing as too difficult

From The State of Open Data survey, 2023

https://figshare.com/articles/dataset/State_of_Open_Data_Survey_2023_additional_resources/24517123?file=43062709

Q: Which of the following circumstances would make it more likely that you would share your data publicly?

N = 6092

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Researchers believe that their data sharing needs are well-served

Not well served, important

Well served, important

Not well served, not important

Well served, not important

From “A Survey of Researchers’ Needs and Priorities for Data Sharing”, Data Science Journal, 2021

10.5334/dsj-2021-031

Data sharing tasks in the survey included:

Deciding what to share
Finding a repository
Writing a data availability statement
Obtaining a DOI
Choosing a licence

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How to support a strong Open Data policy?

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Data sharing should occur before manuscript submission

Data must be in a repository

Data availability statement required

Accessible data

Data must be openly licensed

Data must be FAIR

Reusable data

Datasets must be cited

Credit for data

Peer reviewers access and assess the data as part of the peer review process

This is an overview of our Open Data guidelines at F1000. There are a number of elements which aim to make the data which is shared alongside published articles accessible and reusable.

To ensure that data is Accessible, we require a data availability statement explaining how data can be accessed - the must be stored in a data repository.

Reusable Data must be openly licensed and the data should ideally be shared in a way that complies with the FAIR principles, which are outlined in a later slide.

We also want the data creators to get credit for their data, so datasets should be cited in the body of the article where relevant, and added to the reference list or bibliography.

All of these requirements are checked pre-publication by our editorial team; and the datasets will be assessed by the peer reviewers as part of their evaluation of the research post-publication.

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Resources, webinars, guidelines

https://think.f1000research.com/open-data/toolkit/

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Data details required at manuscript submission

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Article cannot be submitted without providing all details

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Editorial support and checking

Data sharing in appropriate repository

Correct DAS & data citation format

Sensitive data & ethical checks

File formats and licences

Expert (internal)

Editorial teams needed

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How to ensure data is shared openly?

Authors who want to engage with Open Science publishing (still) aren’t necessarily data sharing experts

Many authors will do the minimum required to get published in their chosen journal

Upstream support and guidance help (but you can’t rely on them)

Systems can help to enforce policy

Embedded knowledge in journal editorial teams is key

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