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Galaxies, made up of billions of stars like our Sun, are the beacons that light up the structure of even the most distant regions in space. Not all galaxies are alike, however. They come in very different shapes and have very different properties; they may be large or small, old or young, red or blue, regular or confused, luminous or faint, dusty or gas-poor, rotating or static, round or disky, and they live either in splendid isolation or in clusters. In other words, the universe contains a very colourful and diverse zoo of galaxies. For almost a century, astronomers have been discussing how galaxies should be classified and how they relate to each other in an attempt to attack the big question of how galaxies form. Galaxy Zoo (Lintott et al. 2008, 2011) pioneered a novel method for performing large-scale visual classifications of survey datasets. This webpage allows anyone to download the resulting GZ classifications of galaxies in the project.
EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe