Bridging Disciplines in Data Management Research to Solve Complex Data Problems
Summary: Domain-driven scientific challenges across computational, data-driven and AI-powered paradigms expose core data-management problems — pipeline provenance, scalable spatio-temporal visual exploration, and generalizable data integration. Advocates interdisciplinary, systems-plus-methods research tightly coupled with domain experts to derive fundamental algorithms and deployable systems. (summarized by gpt-5-mini on Feb 09 2026)
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