Jingwei is an interdisciplinary platform for reconstructing long-term, global spatiotemporal variations of dissolved oxygen and other ocean elements from sparse observations. Built on a hybrid deep learning framework, it provides accurate reconstructions of ocean deoxygenation and supports mechanistic understanding of climate-driven ocean change. The name Jingwei comes from a mythical bird in Chinese mythology that persistently fills the sea with pebbles and twigs, echoing our effort to fill the gaps in sparse ocean observations with AI. The platform offers interactive data visualization, resource sharing, and continuous updates toward more ocean biogeochemical variables.

DDE DataExpo is a data discovery and integration system developed under the Deep-time Digital Earth (DDE) Program, the first big science program initiated by the International Union of Geological Sciences. As a key component of the DDE data infrastructure, DataExpo aims to discover, organize, and integrate global geological and Earth science data resources. The system has crawled and indexed more than one million websites using large-scale geoscience keywords and has identified over 200,000 geological data resources, providing a foundation for open, reusable, and knowledge-driven Earth science research.

X-index is a research literature analysis tool developed on the Acemap platform to evaluate the academic value of papers from an interdisciplinary perspective. The system maps research outcomes onto disciplinary coordinate systems and quantitatively measures disciplinary diversity and conceptual novelty. It supports dynamic charts for tracking long-term concept evolution, identifies patterns such as tool-driven research, and provides concept heatmaps and data matrices for tracing cross-disciplinary innovation within large-scale literature collections.