Personnaz A. auteur aut IRD Amer-Yahia S. auteur aut IRD Berti-Equille Laure auteur aut IRD Fabricius M. auteur aut IRD Subramanian S. auteur aut IRD text bookSection eng text/pdf reformatted digital access We demonstrate dora the explorer, a system that guides users in finding items of interest in a very large data set. dora the explorer provides users with the full spectrum of exploration modes and is driven by Data Familiarity or Curiosity, as well as User Interventions. dora the explorer is able to handle data and search scenario complexity, i.e., the difficulty to find scattered/clustered individual records in the data set, and user ability to express what s/he needs. dora the explorer relies on Deep Reinforcement Learning that combines intrinsic (curiosity) and extrinsic (familiarity) rewards. dora's main goal is to support scientific discovery from data. We describe the system architecture and illustrate it with three demonstration scenarios on a 2.6 million galaxies SDSS, a large sky survey data set1. A video of dora the explorer is available at https://bit.ly/dora-demo, the code https://github.com/apersonnaz/rl-guided-galaxy-exploration, and the application at https://bit.ly/dora-application. specialized 122 020 4769-4773 New York ACM 2021 CIKM'21.International Conference on Information and Knowledge Management, 30., [En ligne] (AUS), 2021/11/01-05 https://www.documentation.ird.fr/hor/fdi:010083557 10.1145/3459637.3481967 978-1-4503-8446-9 https://www.documentation.ird.fr/hor/fdi:010083557 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2021-11/010083557.pdf IRD - Base Horizon / Pleins textes 2021-10-21 2021-11-19 fdi:010083557 fre