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      <dc:title>Ontology for Meaning-Driven AI: Grounding, Interpretability, and Trust</dc:title>
      <dc:creator>Han, Myung-Ja K.</dc:creator>
      <dc:creator>Falconer, Josh</dc:creator>
      <dc:creator>Leem, Sumin</dc:creator>
      <dc:creator>Choi, Inkyung</dc:creator>
      <dc:description>Ontologies play a critical role in organizing, connecting, and enabling the reuse of information
across memory institutions and other knowledge domains. As AI systems increasingly generate and consume metadata, ontologies are emerging as essential mechanisms for grounding meaning, supporting interoperability, and building trust. Yet ontology development remains uneven and challenging in AI-enabled environments, requiring new approaches that integrate human expertise, machine reasoning, and scalable workflows. This panel brings together researchers and practitioners to examine how ontology practices are evolving, focusing on design strategies, human–AI collaboration, validation, and the role of ontologies in supporting reliable, interpretable, and reusable knowledge in an AI-driven environment.</dc:description>
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