
compliance checks
Take the guesswork out of open science
Data sharing policies and open science mandates are important—but written policies tend to use broad, inclusive language, without the detailed information researchers need to successfully fulfill requirements. For publishers and funders, screening each piece of research by hand is staff intensive and unsustainable at scale.
DataSeer Compliance Checks analyze individual manuscripts and generate a detailed report tailored to your organization’s specific workflows and requirements, along with customized advice for researchers to follow in revisions.
Compliance Checks ensure your open policies are met and provide evidence of compliance, while freeing your team to focus their expertise where it’s needed most.
Personalize your workflow
How could Compliance Checks work at your organization?
Send manuscript to DataSeer
During Editorial Office checks (either at initial submission or revision) the manuscript is sent to DataSeer for analysis.
DataSeer analysis
DataSeer checks that all datasets are public
That includes verifying links and accession numbers, and examining supporting information files.
Receive a report
DataSeer reports on the datasets and their sharing locations. If data have not been shared, the report provides researchers with advice.
Send a revision
Journal staff include the DataSeer report with the editorial decision letter for the manuscript.
Authors share, revise, and return
Staff may recheck manually, or reupload the revised manuscript to DataSeer to ensure that the requested steps have been completed.
Aligning Science Across Parkinson’s (ASAP) uses DataSeer Compliance monitoring in their standard manuscript screening process. In a 2023 article, the funder reported an improvement in data-sharing rates across revisions from an average of 12% for the first version to 69% for the second version.
see it in action
Aligning Science Across Parkinson’s (ASAP) uses DataSeer Compliance monitoring in their standard manuscript screening process. In a 2023 article, the funder reported an improvement in data-sharing rates across revisions from an average of 12% for the first version to 69% for the second version.

