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A full-fledged data exploration system must combine different accessmodalities with a powerful concept of guiding the user in the explorationprocess, by being reactive and anticipative both for data discovery and fordata linking. Such systems are a real opportunity for our community to cater tousers with different domain and data science expertise. We introduce INODE --an end-to-end data exploration system -- that leverages, on the one hand,Machine Learning and, on the other hand, semantics for the purpose of DataManagement (DM). Our vision is to develop a classic unified, comprehensiveplatform that provides extensive access to open datasets, and we demonstrate itin three significant use cases in the fields of Cancer Biomarker Reearch,Research and Innovation Policy Making, and Astrophysics. INODE offerssustainable services in (a) data modeling and linking, (b) integrated queryprocessing using natural language, (c) guidance, and (d) data explorationthrough visualization, thus facilitating the user in discovering new insights.We demonstrate that our system is uniquely accessible to a wide range of usersfrom larger scientific communities to the public. Finally, we brieflyillustrate how this work paves the way for new research opportunities in DM.

INODE: Building an End-to-End Data Exploration System in Practice [Extended Vision]