EXPLORE’s main objective is to deploy machine learning (ML) and advanced visualization tools to achieve efficient, user-friendly, realistic exploitation of scientific data from astrophysics and planetary space missions, as well as from supporting ground-based massive surveys. We will focus on six different topics, each chosen for their timely importance and their complementary data structures. This diversity and complementarity is key to a future evolution and growth of the platform that will be relevant and applicable to the broadest possible user-base within the research community. Two of EXPLORE’s topics are related to Lunar observation, two to Galactic Science and two to stellar characterization. For each of these topics, the state-of-the-art will be enhanced by introducing ML techniques and advanced visualization tools to support “Human Learning”. Project results will be disseminated to a wide range of targets communities (astronomy, AI, general public, etc) and prepared for submission as scientific papers. For each topic, specific tools will be created, called Scientific Data Application (SDA) throughout this proposal. These SDAs will be developed on a dedicated cloud solution (the EXPLORE Thematic Exploitation Platform, EXPLORE-TEP). This will be made available also on existing cloud platforms such as ESCAPE Science Analysis Platform and the ESA Datalabs, close to the input data, and open to the community for direct exploitation-on-demand. These SDAs will also be used by the consortium to produce enhanced scientific datasets for space science mission exploitation, which will be stored in appropriate archives for public access. Datasets from Gaia and recent lunar (LRO, Clementine, Chandrayaan, etc) space missions are at the core of the EXPLORE project and will be complemented by previous space missions (IUE, Galex, WISE, etc). Data from ground-based surveys (APOGEE, Gaia-ESO, RAVE, etc) will be used to provide added value to the Gaia and Lunar missions.