Call for Papers

The Research Track solicits original and unpublished research contributions on all aspects of Knowledge Graphs and related technologies. Submissions should present significant advances in theories, methodologies, algorithms, systems, applications, or evaluations related to Knowledge Graphs. Topics include, but are not limited to, knowledge representation, ontology engineering, knowledge acquisition, reasoning, graph analytics, knowledge graph construction and maintenance, semantic technologies, and the integration of Knowledge Graphs with AI technologies such as large language models, retrieval-augmented generation, multimodal AI, and agentic systems.

The IJCKG In-Use Track provides a forum to explore the benefits and challenges of applying Knowledge Graph technologies in concrete, practical use cases, in contexts ranging from industry to government and society (e.g., cultural heritage, astrophysics, biodiversity, medicine).

The track aims to give a stage to applied works addressing real-world problems in which Knowledge Graph technologies have been employed, possibly in combination with machine learning, deep learning, large language models, and other AI techniques.

The In-Use Track seeks submissions describing applied research as well as software tools, systems, or architectures that benefit from the use of Knowledge Graph technologies. Importantly, submitted papers should provide convincing evidence of the use of the proposed application or tool by the target user group, preferably outside the group that conducted the development and, more broadly, outside the Knowledge Graph research community.

The IJCKG 2026 Education Track provides a forum for researchers and practitioners to explore the role of Artificial Intelligence (AI) and Knowledge Graphs (KGs) in advancing education, learning, and educational technologies. The track aims to bring together innovative research on AI-driven learning environments, knowledge-enhanced educational systems, and emerging applications of generative AI, retrieval-augmented generation (RAG), and knowledge representation in education.

The Education Track seeks submissions describing theoretical, methodological, and applied research, as well as educational tools, systems, and infrastructures that leverage AI and Knowledge Graph technologies. Topics of interest include AI in Education, Knowledge Graphs for Learning, Generative AI and Educational Applications, Knowledge Representation and Educational Infrastructure, and Evaluation, Interaction Design, and Community Resources for Education.

The IJCKG 2026 Industrial Track provides a premier forum for industry practitioners, engineers, and applied researchers to showcase how Knowledge Graph technologies and AI are creatively deployed to solve complex, real-world problems while actively contributing to human flourishing. Submissions in this track should go beyond theoretical design to describe concrete, deployed industrial use cases, emphasizing creativity, user experience, and the positive impact of these systems on people, organizations, and society.

IJCKG 2026 is pleased to invite submissions to the Poster and Demo Track, which complements the full-paper tracks of the conference. This track provides an opportunity to present late-breaking research results, ongoing research projects, innovative ideas, and work in progress.

Poster and Demo presentations allow researchers to present their work directly to conference participants and receive valuable feedback on significant work in progress, cutting-edge research, emerging ideas, or systems that are best communicated through interactive or visual demonstrations.

We welcome submissions relevant to the field of Knowledge Graphs, including but not limited to the topics covered by the IJCKG 2026 full-paper tracks. Suitable submissions include reports on ongoing or completed research, software systems, idea papers that introduce promising research directions, position papers presenting a bird’s-eye view of a research topic, and PhD thesis abstracts.