openalx-bibliometrics

Retrieve OpenAlex publication metadata and compute bibliometric indices.

33|6|Updated Mar 17, 2026

Search Tags:#openalex #bibliometrics #citation-network #research-trends #h-index #co-authorship #scientometrics

Ready to run

npx skills add https://github.com/xjtulyc/awesome-rosetta-skills --skill openalx-bibliometrics

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: openalx-bibliometrics
Source: https://github.com/xjtulyc/awesome-rosetta-skills/tree/main/skills/21-library-science/openalx-bibliometrics
Command: npx skills add https://github.com/xjtulyc/awesome-rosetta-skills --skill openalx-bibliometrics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, pandas, numpy, networkx, matplotlib, scipy.

What problem does it solve?

This Skill solves the challenge of measuring and visualizing scholarly impact and collaboration using open bibliographic data, without manually downloading and cleaning large datasets.

Core Features & Use Cases

OpenAlex-powered bibliometrics: Fetch publication metadata and compute standard indices like h-index, g-index, and i10-index.
Network and trend analytics: Build co-authorship graphs, analyze citation patterns, and map research trends via concept co-occurrence proxies.
Actionable outputs for comparison: Compare fields or institutions by output, collaboration structure, and citation dynamics to support mapping studies and literature reviews.

Quick Start

Ask the skill to analyze a research query on OpenAlex and produce bibliometric indices plus co-authorship and trend summaries for the returned works.

Frequently Asked Questions about openalx-bibliometrics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I compute h-index and citation network metrics using OpenAlex data?▼

To compute h-index and citation network metrics using OpenAlex data, this skill retrieves publication metadata via paginated HTTP requests and calculates scholarly impact indicators including h-index, g-index, and i10-index using Python data and graph plotting dependencies.

What is the best way to build a co-authorship graph from bibliometric metadata?▼

Building a co-authorship graph from bibliometric metadata involves fetching publication records via the OpenAlex API and applying network metrics workflows to transform structured tables into collaboration network visualizations.

Does this bibliometric analysis approach require installing pandas and networkx?▼

Yes, this bibliometric analysis approach requires installing pandas and networkx, along with requests, numpy, matplotlib, and scipy, to execute network metrics and visualization workflows on OpenAlex publication metadata.

Can I track research trends and concept co-occurrence with OpenAlex API?▼

Yes, you can track research trends and concept co-occurrence with the OpenAlex API by retrieving publication metadata, transforming results into structured tables, and mapping concept co-occurrence proxies to analyze scientific output dynamics.

How do I compare research output across institutions without manually downloading datasets?▼

To compare research output across institutions without manual dataset downloads, this skill retrieves citation metadata directly from the OpenAlex API and computes comparative scholarly impact indicators and collaboration structures.