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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 Australian National University undertake work to collect and publish metadata about research data held by ANU, and in the case of four discipline areas, Earth Sciences, Astronomy, Phenomics and Digital Humanities to develop pipelines and tools to enable the publication of research data using a common and repeatable approach. Aims and outcomes: To identify and describe research data held at ANU, to develop a consistent approach to the publication of metadata on the University's data holdings: Identification and curation of significant orphan data sets that might otherwise be lost or inadvertently destroyed, to develop a culture of data data sharing and data re-use.
The ProteomeXchange consortium has been set up to provide a single point of submission of MS proteomics data to the main existing proteomics repositories, and to encourage the data exchange between them for optimal data dissemination. Current members accepting submissions are: The PRIDE PRoteomics IDEntifications database at the European Bioinformatics Institute focusing mainly on shotgun mass spectrometry proteomics data PeptideAtlas/PASSEL focusing on SRM/MRM datasets.
The WDC has a FTP-server to distribute the PCN index derived from the geomagnetic observatory Qaanaaq (THL) and the Kp-index data products derived at the geomagnetic observatory Niemegk (NGK). The WDC is also holding extensive archives of magnetograms and other geomagnetic observatory data products that predate the introduction of digital data recording. The material is in analogue form such as film or microfiche. The Polar Cap index (abbreviation PC index) consists of the Polar Cap North (PCN) and the Polar Cap South (PCS) index, which are derived from magnetic measurements taken at the geomagnetic observatories Qaanaaq (THL, Greenland, +85o magnetic latitude) and Vostok (VOS, Antarctica, -83o magnetic latitude), respectively. The idea behind these indices is to estimate the intensity of anti-sunward plasma convection in the polar caps. This convection is associated with electric Hall currents and consequent magnetic field variations perpendicular to the antisunward plasma flow (and related Hall current) which can be monitored at the Qaanaaq and Vostok magnetic observatories. PC aims at monitoring the energy input from solar wind to the magnetosphere (loading activity). The index is constructed in such a way that it has a linear relationship with the merging Electric Field at the magnetopause; consequently PC is given in units of mV/m as for the electric field. In August 2013, the International Association of Geomagnetism and Aeronomy (IAGA) endorsed the PC index. The endorsed PC index is accessible at pcindex.org or through WDC Copenhagen.
The University of Guelph Research Data Repositories provide long-term stewardship of research data created at or in cooperation with the University of Guelph. The Data Repositories are guided by the FAIR Guiding Principles for scientific data management and stewardship which aim to improve the Findability, Accessibility, Interoperability and Reuse of research data. The Data Repositories is composed of two main collections: the Agri-environmental Research Data collection which houses agricultural and environmental research data, and the Cross-disciplinary Research Data collection which houses all other disciplinary research data.