# Open Research Knowledge Graph:A System Walkthrough

arXiv: https://arxiv.org/abs/2206.01439 · HTML: https://mlsanity.com/paper/2206.01439/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2022.

## Built on by (most cited first, 5 of 5)

- [Contri(e)ve: Context + Retrieve for Scholarly Question Answering](https://mlsanity.com/paper/2409.09010/) (2024)
- [Beyond the Numbers: Transparency in Relation Extraction Benchmark Creation and Leaderboards](https://mlsanity.com/paper/2411.05224/) (2024)
- [Open-Source Agentic Hybrid RAG Framework for Scientific Literature Review](https://mlsanity.com/paper/2508.05660/) (2025)
- [paper.json: A Coordination Convention for LLM-Agent-Actionable Papers](https://mlsanity.com/paper/2605.16194/) (2026)
- [BizSage: A Self-Evolving Multi-Agent Framework for Business Research with Efficient Knowledge Retrieval](https://mlsanity.com/paper/2609.22235/) (2026)

## Abstract (arXiv)

Despite improved digital access to scholarly literature in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. Scholarly knowledge remains locked in representations that are inadequate for machine processing. The Open Research Knowledge Graph (ORKG) is an infrastructure for representing, curating and exploring scholarly knowledge in a machine actionable manner. We demonstrate the core functionality of ORKG for representing research contributions published in scholarly articles. A video of the demonstration and the system are available online.