Satellite remote sensing has emerged as an essential and necessary observing system to acquire global information about the state of the ocean. Complemented with in situ observing networks, the ultimate goals are to be able to make accurate estimates of selected key sets of geophysical variables, with the intention of either making operational predictions across time and spatial boundaries, or advancing fundamental knowledge through development of empirical relationships and theoretical models. For satellite oceanography, improvements are then constantly being sought in our understandings of the geophysical processes, the sensor physics, the electromagnetic and microwave properties and interactions at the complex air-sea interface. Challenges appear as unlimited as the variety of sea surface dynamics and boundary layer meteorological conditions with their broad range of spatial and temporal scales across the globe. To face these challenges, numerous efforts took places over the passed decade to build an ever-increasing quality, quantity, duration and integration of ocean observations. In parallel, simulation capabilities largely improved. All these efforts are then all critically calling for improved methodologies to better structure the wealth of information that is made readily accessible. This latter aspect is a very demanding new component for future multidisciplinary scientific research. Major innovations to consolidate sensor data repositories, to automate tailored queries, to extract, reveal and quantify relationships will then closely associate computer science developments and applied statistics with comprehensive theoretical and experimental thematic studies.