# Usage of OpenAlex for creating meaningful global overlay maps of science on the individual and institutional levels

arXiv: https://arxiv.org/abs/2404.02732 · HTML: https://mlsanity.com/paper/2404.02732/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Apr 2024.

## Built on by (most cited first, 2 of 2)

- [LitBench: A Graph-Centric Large Language Model Benchmarking Tool For Literature Tasks](https://mlsanity.com/paper/2603.00051/) (2026)
- [From Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analytics](https://mlsanity.com/paper/2607.21327/) (2026)

## Abstract (arXiv)

Global overlay maps of science use base maps that are overlaid by specific data (from single researchers, institutions, or countries) for visualizing scientific performance such as field-specific paper output. A procedure to create global overlay maps using OpenAlex is proposed. Six different global base maps are provided. Using one of these base maps, example overlay maps for one individual (the first author of this paper) and his research institution are shown and analyzed. A method for normalizing the overlay data is proposed. Overlay maps using raw overlay data display general concepts more pronounced than their counterparts using normalized overlay data. Advantages and limitations of the proposed overlay approach are discussed.