Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge
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Abstract (arXiv)
Despite improved digital access to scholarly knowledge in recent decades, scholarly communication remains exclusively document-based. In this form, scholarly knowledge is hard to process automatically. In this paper, we present the first steps towards a knowledge graph based infrastructure that acquires scholarly knowledge in machine actionable form thus enabling new possibilities for scholarly knowledge curation, publication and processing. The primary contribution is to present, evaluate and discuss multi-modal scholarly knowledge acquisition, combining crowdsourced and automated techniques. We present the results of the first user evaluation of the infrastructure with the participants of a recent international conference. Results suggest that users were intrigued by the novelty of the proposed infrastructure and by the possibilities for innovative scholarly knowledge processing it could enable.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Jan 2019.
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Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 3.
4 papers.
- 2023SemOpenAlex: The Scientific Landscape in 26 Billion RDF Triplescited by 12
- 2026Lacuna: A Research Map for Machine Learningcited by 2
- 2026Large Knowledge Model: From Papers to a Scientific Reasoning Landscapecited by 1
- 2026From Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analyticscited by 0
- 2026Large Knowledge Model: From Papers to a Scientific Reasoning Landscape23 Sep 2026
- 2026From Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analytics23 Jul 2026
- 2026Lacuna: A Research Map for Machine Learning24 Jun 2026
- 2023SemOpenAlex: The Scientific Landscape in 26 Billion RDF Triples7 Aug 2023