Explore academic impact - without flattening it into a rank.

Rankless visualizes the global flow of ideas across universities, journals, scholars, and countries - revealing who influences whom, where knowledge travels, and which topics bind the world together.

Spotlights

Jump straight into examples across institutions, countries, journals, and scholars.

Universities

Explore institutional impact

Influence by field, geography, and collaboration networks.

Scholars

Individual trajectories

Track citation origins and topical niches across careers.

Countries

See where knowledge travels

Which countries cite which - and on what topics.

Journals

Field-shaping venues

Topical breadth, citation reach, and cross-disciplinary bridges.

How does Rankless work?

Under the hood, Rankless combines open bibliographic data, network science, and interactive design to surface context that rankings miss.

Data pipeline

OpenAlex + enhancements

We build on OpenAlex snapshots and enrich with journal metrics and curated identifiers to create a comprehensive citation graph.

Networks

Citations, topics, collaborations

Rankless constructs multi-layer graphs to show influence by domain, geography, and co-authorship - so you can follow the story behind the metrics.

Exploration

Click to go deeper

Every chart and map is explorable. Click to jump from a bird’s-eye view to institutions, journals, and scholars shaping a field.

Why Rankless?

We need to understand more and rank less.

Rankings flatten complexity into a single number. Rankless restores the context: domain, geography, collaboration, and time. Use it to make better-informed decisions - whether you’re a student, researcher, policymaker, or funder.

Rankless is an experimental data visualization project that allows users to explore the impact of thousands of universities. It is built on the idea that universities generate impact that is specific to a geography and to certain topics, and that rankings obscure that impact by reducing it to a single dimension. By transcending rankings, we highlight a university’s multidimensional impact by showing you who they work with and who cites them. To understand more, sometimes, we need to rank less.

Who’s behind it?

Rankless is created by the Center for Collective Learning (CCL) at Corvinus University of Budapest, with a small, multidisciplinary team.

Endre Borza
Engineering

Endre Borza

Research Data Engineer & Lead Developer

Máté Barkóczi
Design

Máté Barkóczi

Graphic & Interaction Design

Veronika Hamar
Operations

Veronika Hamar

Executive Director, CCL

César A. Hidalgo
Director

César A. Hidalgo

Director, CCL

Rankless was developed at the Center for Collective Learning (CCL) at Corvinus University of Budapest by a team of four people. The main person behind the project is Endre Borza, an economist working as a data engineer who constructed Rankless from the ground up. The graphic and interaction design of Rankless is the work of Máté Barkóczi, a designer working on his Master’s at MOME and as an intern at CCL. Vera Hamar, Executive Director of CCL, supported Rankless as a project manager and coordinator. César A. Hidalgo, Director of CCL, supervised the project.

The Center for Collective Learning (CCL) is an interdisciplinary research laboratory with offices in Toulouse, France and Budapest, Hungary. For more than a decade, CCL has advanced the state of the art in economic development, data visualization, and applications of artificial intelligence. Previous data visualization projects by members of CCL include The Observatory of Economic Complexity, Pantheon, and Data USA, among dozens of others.

Rankless was created at the Center for Collective Learning at the Corvinus Institute for Advanced Studies (CIAS) at Corvinus University in Budapest. This project was supported by the Learn Data ERA Chair from the European Research Executive Agency.

Contact

You can reach us by contacting Veronika and Endre directly @ rankless@​centerforcollectivelearning.org

Frequently Asked Questions

Questions and answers about data sources used, update frequency, filtering, impact measurement, extensions and visualization.

We use open, up-to-date data, process it with transparent methods and visualize the results in an intuitive, unique way.

What are your data-sources?


What are indexed citations?


Can I download/export Rankless data?


How often do you update your data?


How accurate is your data?


Do you filter the data?


How do you assign papers and journals to subject categories?


How do you measure impact?


What kind of visualization engine do you use?


How do you measure specialization?


Created by

Rankless by CCL
2025