The field of knowledge representation and ontology alignment is witnessing significant developments, driven by the need for more efficient and effective ways to manage and utilize knowledge in various domains. Researchers are exploring new approaches to represent and align ontologies, leveraging techniques such as knowledge graphs, reasoning, and natural language processing. A key trend is the development of more robust and scalable tools for ontology alignment, enabling better integration of heterogeneous knowledge systems. Additionally, there is a growing focus on creating more transparent and explainable decision-making processes, particularly in resource allocation and knowledge governance. Noteworthy papers include:

• Intanify AI Platform, which introduces a novel platform for automated IP audit and due diligence, embedding AI and knowledge graphs to support SMEs in extracting value from their intangible assets.
• OntoAligner, a comprehensive Python toolkit for ontology alignment, designed to address current limitations in scalability, modularity, and ease of integration with recent AI advances.