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Proposed sessions

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1. Spatial Association

   Yongze Song

   This session invites researchers to present the latest studies in spatial association methods and their practical applications. Accurate characterization of spatial association is fundamental for exploring spatial factors, improving spatial predictions, and supporting informed geographical decision-making. Models addressing spatial dependence, heterogeneity, geocomplexity, singularity, and similarity are central to describing spatial association. Moreover, recent developments in geospatial artificial intelligence have introduced powerful and precise approaches for analyzing spatial association. We welcome submissions from both theoretical and applied studies that contribute to the advancement of spatial association analysis.
2. Ontologies, Knowledge Graphs, and Large Language Models in Geoscience: Construction and Application

   Xiaogang Ma, Chengbin Wang, Anirudh Prabhu

   As the geoscience community increasingly turns to advanced AI methods, the integration of ontologies, knowledge graphs, and large language models (LLMs) offers transformative potential for data management and knowledge discovery. This session aims to explore innovative approaches to constructing and applying these technologies within geoscience. We invite presentations that demonstrate the development of ontologies and knowledge graphs specific to geoscientific domains, showcasing how these models and frameworks can enhance data interoperability and semantic clarity. In particular, we welcome presentations that demonstrate how the machine-readable semantics are leveraged in reasoning and inference tasks that lead to new knowledge discoveries. Moreover, we encourage discussions on the utilization of LLMs for data science tasks in geoscience, such as automation of literature review, hypothesis generation, and enhanced data querying and analysis. Other presentations such as using knowledge graph to guide and advise LLMs in data-intensive research are also encouraged. By bringing together experts in geoinformatics, artificial intelligence, and mathematical geosciences, this session aims to stimulate interdisciplinary dialogue and identify best practices for leveraging these advanced tools. Join us in exploring and discussion how the synergistic application of ontologies, knowledge graphs, and LLMs can advance a variety of topics in geoscience.
3. AI-driven Mineral Prospectivity Modeling

   Emmanuel John Carranza, Renguang Zuo

   Mineral prospectivity modeling as a computer-based approach to delineate target areas for exploration of certain mineral deposits in a mineral system has evolved from being knowledge driven to artificial intelligence (AI)-driven. The applications of AI in mineral exploration are ever increasing nowadays to address the complexity of relationships among datasets and with known deposit occurrences. The session welcomes submissions for presentations of: (1) novel AI algorithms and applications for recognition and integration of geo-anomalies to support mineral exploration, in 2D or 3D; and (2) novel AI algorithms and applications for analysis and synthesis of a variety of geoscience datasets to model mineral prospectivity and associated uncertainty, in 2D or 3D.
4. Regina's Test Session

   Regina van den Boogaart

   That is a test session proposal. Test 123 Test Test 123 Test Test 123 Test Test 123 TestTest 123 Test Test 123 Test Test 123 Test Test 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 TestTest 123 Test