Taking the guesswork out of data sharing

Data sharing advice for your datasets and your articles

Our goal is to move data sharing away from broadly worded policies and guidelines, and instead show researchers what they need to do with the datasets from their particular manuscript.

By focusing on individual articles, DataSeer give researchers a clear picture of:

  1. Which datasets from that particular article they need to share 
  2. What format they should be in 
  3. Which repository is most suitable 

Advice for each type of data is drawn from our wiki, which you’re welcome to edit.

workflow example

Here’s our workflow for an individual article:

User uploads some
research text
DataSeer finds sentences describing data collection
DataSeer gives advice on sharing that type of data
user shares data & gives
accession IDs
DataSeer generates data accessibility statement
DataSeer sends report to journal or funder

What are data collection sentences?


We’re focused here on the steps the researcher took to get the data onto their computer, rather than any data manipulation steps they took after that.

[10 second video of highlighting a data sentence in a text, animates on mouse hover, still image is last image in sequence – Use Jess’s SNP sentence]

Use Cases for DataSeer

DataSeer for Journal Managers

Journals can use DataSeer to help their authors comply with their data sharing policies. A simple email-based integration is available for most major manuscript management systems, and requires only the addition of a few email templates in the journal system.

DataSeer for Funders & Institutions

DataSeer can also be applied to published articles, allowing stakeholders like institutions and funders to promote data sharing among their researchers and assess compliance with their data policies.