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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.
University of Alberta Dataverse is a service provided by the University of Albert Library to help researchers publish, analyze, distribute, and preserve data and datasets. Open for University of Alberta-affiliated researchers to deposit data.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
Queen's University Dataverse is the institutional open access research data repository for Queen's University, featuring Queen's University Biological Station (QUBS) which includes research related to ecology, evolution, resource management and conservation, GIS, climate data, and environmental science.
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.