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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.
The US Virtual Astronomical Observatory (VAO) is the VO effort based in the US, and it is one of many VO projects currently underway worldwide. The primary emphasis of the VAO is to provide new scientific research capabilities to the astronomy community. Thus an essential component of the VAO activity is obtaining input from US astronomers about the research tools that are most urgently needed in their work, and this information will guide the development efforts of the VAO. >>>!!!<<< Funding discontinued in 2014 and all software, documentation, and other digital assets developed under the VAO are stored in the VAO Project Repository https://sites.google.com/site/usvirtualobservatory/ . Code is archived on Github https://github.com/TomMcGlynn/usvirtualobservatory . >>>!!!<<<
EMSC collects real time parametric data (source parmaters and phase pickings) provided by 65 seismological networks of the Euro-Med region. These data are provided to the EMSC either by email or via QWIDS (Quake Watch Information Distribution System, developped by ISTI). The collected data are automatically archived in a database, made available via an autoDRM, and displayed on the web site. The collected data are automatically merged to produce automatic locations which are sent to several seismological institutes in order to perform quick moment tensors determination.
PDBe is the European resource for the collection, organisation and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - we work to collate, maintain and provide access to the global repository of macromolecular structure data. We develop tools, services and resources to make structure-related data more accessible to the biomedical community.
The GTN-P database is an object-related database open for a diverse range of data. Because of the complexity of the PAGE21 project, data provided in the GTN-P management system are extremely diverse, ranging from active-layer thickness measurements once per year to flux measurement every second and everthing else in between. The data can be assigned to two broad categories: Quantitative data which is all data that can be measured numerically. Quantitative data comprise all in situ measurements, i.e. permafrost temperatures and active layer thickness (mechanical probing, frost/thaw tubes, soil temperature profiles). Qualitative data (knowledge products) are observations not based on measurements, such as observations on soils, vegetation, relief, etc.