Top Level Ontology
Top-level ontologies provide a standardized, high-level framework for organizing and representing knowledge across diverse domains, aiming to improve data interoperability and facilitate knowledge sharing. Current research emphasizes using ontologies to enhance explainability in complex systems like multimodal large language models and to improve the efficiency of tasks such as ontology versioning and knowledge graph construction, often leveraging techniques like ontology matching and rule-based reasoning. This work has significant implications for various fields, enabling more robust and reliable AI systems, improved data management in scientific research, and more efficient knowledge discovery across diverse applications.
Papers
EDUKG: a Heterogeneous Sustainable K-12 Educational Knowledge Graph
Bowen Zhao, Jiuding Sun, Bin Xu, Xingyu Lu, Yuchen Li, Jifan Yu, Minghui Liu, Tingjian Zhang, Qiuyang Chen, Hanming Li, Lei Hou, Juanzi Li
Ontology Development is Consensus Creation, Not (Merely) Representation
Fabian Neuhaus, Janna Hastings