Give your datasets
the credit they deserve.

Scholar Data helps you measure, improve, and showcase the impact of your datasets, similarly to how you track publication impact on Google Scholar.

Create your profile

Claim your datasets

Find your datasets from our index of 49 million datasets and add them to your profile.

Track your S-index

Showcase this new metric that measures your data sharing impact, the way the h-index measures your publications.

See it in action

Curious what your profile would look like?

Browse an example profile to see how datasets, citations, FAIR scores, and your S-index are displayed.

Trusted by a growing community of researchers

Scholar Data helps researchers measure, discover, and showcase their data sharing impact at scale.

35+

Researcher Accounts

Profiles created and actively managed by real researchers and teams.

49M+

Datasets Indexed

Datasets processed, scored, and tracked for citations and impact across disciplines.

NIH

Challenge Finalist

Recognized as a Phase 1 finalist in the NIH Challenge to incentivize data sharing.

Why it matters

Data sharing goes unrecognized and unrewarded.

Researchers invest years collecting and sharing datasets that underpin reproducibility, transparency, and discovery across every field. Without shared data, findings can't be verified, built upon, or trusted. And yet, the metrics that define academic careers, such as citations, h-index, and impact factor, only count publications. Data sharing goes unrecognized and unrewarded.

This creates a broken incentive: researchers are expected to share data, but get no credit for doing so. The result is that data sharing is treated as a chore rather than a contribution.

Scholar Data and the S-index are aimed at fixing this. By measuring how impactful your datasets are, the S-index gives data sharing the same visibility and recognition as publishing, turning it from an obligation into a career asset.

How the S-index works

A metric built on three signals

The S-index evaluates your data sharing impact by combining dataset-level signals that reflect how findable, reusable, and influential your datasets are across science.

FAIRness

How findable, accessible, interoperable, and reusable each dataset is, scored via F-UJI.

Citations

Direct citations tracked across OpenAlex, Make Data Count, and DataCite.

Mentions

Alternative mentions in code (Software Heritage, Hugging Face), patents, and policies.

Built openly on trusted infrastructure

We don't reinvent the wheel.

Scholar Data is free to use. Our source code is open on GitHub, and our methodology is fully documented.

We transparently aggregate signals from the infrastructure that the research community already relies on.

Explore the platform

Scholar data allows you to do a lot more.

Browse profiles

Find and view author profiles with their S-index, dataset impact metrics, and citation history.

Browse datasets

Explore the impact pages of the 49M datasets we have processed, including their Dataset Index and FAIR scores.

Evaluate a dataset

Drop a DOI or URL and we will generate an impact page for any dataset on the fly.

Integrate with Scholar Data

Repository maintainer? Embed Dataset Index scores and impact metrics directly in your platform.

Give your datasets the credit they deserve.