Rules, ontologies and other logic-based forms of knowledge representation are increasingly used to represent and reason over graph-based data and knowledge. Such representations and reasoning processes may operate under different assumptions (e.g., open vs. closed world assumptions, unique vs. non-unique name assumptions), may aim to represent diverse types of knowledge (e.g., encyclopaedic, procedural, common-sense, etc.), may have different purposes (e.g., classification, execution, consistency-checking, validation, etc.), but all are based on the idea of capturing real-world phenomena via logic-based, machine-readable languages and processes. Such techniques are increasingly seen as a more explainable and more precise alternative to machine learning processes, and are being increasingly combined with such processes to build more reliable AI systems.

In this Special Issue, we solicit submission of original research, survey and resources articles in the scope of TGDK (graph-based data and knowledge) relating more specifically to the application of rules and logic-based reasoning processes.

Scope

In the specific context of graph-based data and knowledge, we solicit submissions on sub-topics that include, but are not limited to:

• Ontologies and Semantic Web
  • Ontology-based data access
  • Rules for knowledge graph creation
  • Rules for knowledge graph embeddings and ontology learning
  • Data interoperability for the Semantic Web
• Rules meet AI for Graphs
  • Combining rules / ontologies, LLMs and graphs
  • Machine learning representations involving rules and graphs
  • Explainable AI approaches based on rules and graphs
  • FAIRness approaches based on rules and graphs
  • AI alignment based on rules and graphs.
  • Agentic AI based on rules and graphs
• Logics for Graphs
  • Non-classical logics for graphs
  • Description Logics, existential rules for graphs
  • Higher-order logics and modal rules for graphs
  • Logic programming, ASP, and Datalog for graphs
  • Rule-based argumentation for graphs
  • Agentic, rule-based approaches using graphs
• Reasoning Systems for Graphs
  • Inconsistency-tolerant rule reasoning for graphs
  • Reasoning with incomplete, inconsistent and uncertain data for graphs
  • Streaming data and complex event processing over graphs
  • Non-monotonic, common-sense, and closed-world reasoning for graphs
  • Scalable and efficient reasoning over graphs
  • Rule-based data quality and benchmarks for graphs
• Rules and Interoperability
  • Rule markup languages and standards for graphs
  • Rule-based policies, reputation, and trust for graphs
  • Rule-based mapping languages for graphs
• Constraints and Schema
  • Shapes for knowledge graphs
  • Validating schema languages for graphs
  • Mining constraints and schemata from graphs
  • Repair strategies for graphs
  • Closed-world reasoning for graphs
  • Certain answers for graph databases
• Ontologies, Rules and Graphs for
  • Climate change monitoring, mitigation & adaptation
  • Environmental protection
  • Supply-chain analysis
  • Agriculture and agri-food
  • Healthcare and life sciences
  • Equity and social welfare
  • Law, regulation, and finance
  • Privacy, security and access control
  • Digital Twins
  • Industrial contexts
  • Production & business rule systems

Guest Editors

• Aidan Hogan, University of Chile, Chile
• Ken Satoh, National Institute of Informatics, NII, Japan
• Ahmet Soylu, Kristiania University of Applied Sciences, Norway

Timeline

• Submissions: September 14, 2026
• Author Notifications: December 14, 2026
• Revisions: January 26, 2027
• Author Notifications: March 26, 2027
• Publication: Q2/Q3, 2027

Submission

Please follow the the submission instructions for TGDK and select the corresponding Special Issue.

As a Diamond Open Access journal, official versions of accepted papers (as accessible via DOI) are published and made available for free online without fees for authors nor readers.