Eye Imaging Dataset Classification Survey

Thank you for taking the time to participate in this survey. We truly appreciate your contribution.

This survey is being conducted as part of the development of the Envision Portal, a platform aimed at improving the discoverability and reuse of eye imaging data. This work is carried out by the FAIR Data Innovations Hub.

The purpose of this survey is to conduct human review of records to determine whether they describe an eye imaging dataset or not. The results will support the development of an AI model that performs this classification automatically from text metadata and will be used to identify true eye imaging datasets from mislabeled records (papers, tables, software, unrelated datasets, etc.) before they are indexed in the Envision Portal.

Although you can complete the survey at any time, we would appreciate it if you could complete at least 100 evaluations (or more, if you can; there are 356 evaluations in total). You will be provided with a Reviewer ID when you first start, and you can use it to come back to the survey at any time, including from a different device, and continue where you left off.

Please note that this survey is completely anonymous. We do not collect any personal identifiable information. Each respondent is assigned a random unique ID, which allows us to compute aggregate statistics when reporting results in future publications.

If you have any questions, feedback, or would like to learn more about this work, please feel free to reach out at bpatel@calmi2.org.