Open Data
Open data initiatives aim to make datasets publicly accessible, fostering collaboration and innovation across various fields. Current research focuses on improving data findability through automated tagging using large language models and developing high-quality, multi-attribute datasets for diverse applications, including urban planning, healthcare, and environmental monitoring. These efforts leverage machine learning techniques, such as graph neural networks and XGBoost, to analyze and interpret open data, ultimately contributing to more robust and reproducible scientific findings and improved decision-making in numerous sectors.
Papers
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