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Found 473 result(s)
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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.
LibraData is a place for UVA researchers to share data publicly. It is UVA's local instance of Dataverse. LibraData is part of the Libra Scholarly Repository suite of services which includes works of UVA scholarship such as articles, books, theses, and data.
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OpenAgrar is an open access repository which publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains amongst others theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews.
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
The NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
PSI Open Data Provider allows users to consult open data related to experiments carried out at PSI. Data made available includes scientific datasets collected during experiments and publications if any. Users can search for data based on related metadata (both their own data and other people's public data).
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An institutional repository at Graz University of Technology to enable storing, sharing and publishing research data, publications and open educational resources. It provides open access services and follows the FAIR principles.
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The National High Energy Physics Science Data Center (NHEPSDC) is a repository for high-energy physics. In 2019, it was designated as a scientific data center at the national level by the Ministry of Science and Technology of China (MOST). NHEPSDC is constructed and operated by the Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences (CAS). NHEPSDC consists of a main data center in Beijing, a branch center in Guangdong-Hong Kong-Macao Greater Bay Area, and a branch center in Huairou District of Beijing. The mission of NHEPSDC is to provide the services of data collection, archiving, long-term preservation, access and sharing, software tools, and data analysis. The services of NHEPSDC are mainly for high-energy physics and related scientific research activities. The data collected can be roughly divided into the following two categories: one is the raw data from large scientific facilities, and the other is data generated from general scientific and technological projects (usually supported by government funding), hereafter referred to as generic data. More than 70 people work in NHEPSDC now, with 18 in high-energy physics, 17 in computer science, 15 in software engineering, 20 in data management and some other operation engineers. NHEPSDC is equipped with a hierarchical storage system, high-performance computing power, high bandwidth domestic and international network links, and a professional service support system. In the past three years, the average data increment is about 10 PB per year. By integrating data resources with the IT environment, a state-of-art data process platform is provided to users for scientific research, the volume of data accessed every year is more than 400 PB with more than 10 million visits.
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The GISAID Initiative promotes the international sharing of all influenza virus sequences, related clinical and epidemiological data associated with human viruses, and geographical as well as species-specific data associated with avian and other animal viruses, to help researchers understand how the viruses evolve, spread and potentially become pandemics. *** GISAID does so by overcoming disincentives/hurdles or restrictions, which discourage or prevented sharing of influenza data prior to formal publication. *** The Initiative ensures that open access to data in GISAID is provided free-of-charge and to everyone, provided individuals identify themselves and agree to uphold the GISAID sharing mechanism governed through its Database Access Agreement. GISAID calls on all users to agree to the basic premise of upholding scientific etiquette, by acknowledging the originating laboratories providing the specimen and the submitting laboratories who generate the sequence data, ensuring fair exploitation of results derived from the data, and that all users agree that no restrictions shall be attached to data submitted to GISAID, to promote collaboration among researchers on the basis of open sharing of data and respect for all rights and interests.
THIN is a medical data collection scheme that collects anonymised patient data from its members through the healthcare software Vision. The UK Primary Care database contains longitudinal patient records for approximately 6% of the UK Population. The anonymised data collection, which goes back to 1994, is nationally representative of the UK population.
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HIstome: The Histone Infobase is a database of human histones, their post-translational modifications and modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics, Indian Institute of Science Education and Research (IISER), Pune.
This project is an open invitation to anyone and everyone to participate in a decentralized effort to explore the opportunities of open science in neuroimaging. We aim to document how much (scientific) value can be generated from a data release — from the publication of scientific findings derived from this dataset, algorithms and methods evaluated on this dataset, and/or extensions of this dataset by acquisition and incorporation of new data. The project involves the processing of acoustic stimuli. In this study, the scientists have demonstrated an audiodescription of classic "Forrest Gump" to subjects, while researchers using functional magnetic resonance imaging (fMRI) have captured the brain activity of test candidates in the processing of language, music, emotions, memories and pictorial representations.In collaboration with various labs in Magdeburg we acquired and published what is probably the most comprehensive sample of brain activation patterns of natural language processing. Volunteers listened to a two-hour audio movie version of the Hollywood feature film "Forrest Gump" in a 7T MRI scanner. High-resolution brain activation patterns and physiological measurements were recorded continuously. These data have been placed into the public domain, and are freely available to the scientific community and the general public.
The ASEP Data Repository is an institutional multidisciplinary on-line repository that stores scientific outputs - bibliographic records, full texts and datasets of the institutional authors from The Czech Academy of Sciences. The repository is hosted by Library of the Czech Academy of Sciences. Data that are stored in database are accessible in the on-line catalogue. Each dataset has its own description and metadata according to international standards.
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The AMUReD Institutional Research Data Repository of the Adam Mickiewicz University in Poznan (UAM) collects and provides access to digital versions of research data collected, processed or produced as part of the scientific research or developmental work of UAM employees.The AMUReD Repository is part of the AMU Research Portal, with University Library in Poznan as the operating unit. Depositing data is possible after logging into the AMU Research Portal, according to the attached instructions. The AMUReD repository is open, and research data are made available in three models: open (Open Access), embargo (Embargo) and closed (Restricted Access). The detailed rules of the AMUReD repository are defined in the Regulations. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The AMUReD repository complies with the FAIR Principles. Each dataset is given a unique DOI identifier. The prefix for DOIs is doi:10.60629. It is possible to choose a Creative Commons license for shared datasets.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
CERIC Data Portal allows users to consult and manage data related to experiments carried out at CERIC (Central European Research Infrastructure Consortium) partner facilities. Data made available includes scientific datasets collected during experiments, experiment proposals, samples used and publications if any. Users can search for data based on related metadata (both their own data and other peoples' public data).
The Radio Telescope Data Center (RTDC) reduces, archives, and makes available on its web site data from SMA and the CfA Millimeter-wave Telescope. The whole-Galaxy CO survey presented in Dame et al. (2001) is a composite of 37 separate surveys. The data from most of these surveys can be accessed. Larger composites of these surveys are available separately.
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.