{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T16:10:12Z","timestamp":1756829412132,"version":"3.44.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686172","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,28]]},"abstract":"<jats:p>In recent developments of AI, we see an increasing augmentation of neural models with unstructured data (RAG), structured data (Graph RAG) and even agents, reasoning services and APIs (Agentic AI). In the evolving landscape of scientific knowledge management, the integration of neuro-symbolic and agentic AI approaches offers opportunities to enhance the organization, discovery, and synthesis of research contributions. We explore how knowledge graphs and large language models (LLMs) can be synergistically combined to advance the representation and accessibility of scholarly knowledge. At the heart of this approach is the Open Research Knowledge Graph (ORKG)\u2014a platform that structures scientific knowledge into machine-readable representations, enabling comparative analyses, automated reasoning, and contextualized exploration of research findings. Extending this vision, ORKG ASK introduces a novel query and synthesis system, combining symbolic knowledge with neural AI capabilities to provide precise, explainable, and interactive responses to complex scientific inquiries. We will examine the foundations and practical applications of agentic and neuro-symbolic AI in scholarly knowledge organization. By bridging the gap between symbolic representations, agentic tools and neural models, this approach aims to make scientific knowledge more accessible, transparent, and actionable\u2014paving the way for a new era of AI-driven research assistance.<\/jats:p>","DOI":"10.3233\/faia250477","type":"book-chapter","created":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T15:33:22Z","timestamp":1756827202000},"source":"Crossref","is-referenced-by-count":0,"title":["Towards Agentic AI \u2013 Neuro-Symbolic Organization of Research Contributions with Knowledge Graphs and Large Language Models"],"prefix":"10.3233","author":[{"given":"S\u00f6ren","family":"Auer","sequence":"first","affiliation":[{"name":"Leibniz University Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Formal Ontology in Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250477","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T15:33:22Z","timestamp":1756827202000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250477"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,28]]},"ISBN":["9781643686172"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250477","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,28]]}}}