Making a Data Nugget

We will work with you along the way to create a Data Nugget from your own research and data! Each Data Nugget goes through an iterative development process, which involves peer-review, classroom piloting, and teacher feedback. It is very common for us to send a lot of edits and feedback on the first round after submission! Our Data Nuggets team works individually with you, the scientist, to help identify the story in your data and communicate effectively with a diverse audience. By going through this process, you will hone your science communications skills, share your research with thousands of students, and increase your broader impacts!

We encourage anyone to make a Data Nugget, and ask that you contact us once you begin this process. We will host your activity on our website, which reaches tens of thousands of educators across the world. Once posted, we can provide page analytics and teacher feedback to share with funding agencies.

If you plan to include Data Nuggets in a Broader Impacts section of a grant, please contact us and we will be happy to write a letter of support or provide some text describing the impacts that your Data Nugget will have on science education and data literacy.

Writing & Submitting Your Data Nugget

  • Download the template for experimental or observational studies and look over the items necessary to create a Data Nugget activity. Text in red must be provided by the researcher, along with images of the research being conducted, a table of data, and graphs or figures of the data.

  • To submit your Data Nugget for review, email the completed document to You will hear back from us shortly with comments and edits. Keep in mind, it is typical that each Data Nugget goes through several rounds of revision before being posted to our site, and this process may take weeks to months.

  • If you are feeling stuck creating your Data Nugget, feel free to contact us or check out our resource page here.

Our experimental template works best for manipulative studies directly testing a hypothesis.

Our observational template works best for observational or community science datasets.