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Found 15 result(s)
The figshare service for the University of Sheffield allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item receives a Digital Object identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as ā€œOpen Services.ā€
Additionally to the institutional repository, current St. Edward's faculty have the option of uploading their work directly to their own SEU accounts on stedwards.figshare.com. Projects created on Figshare will automatically be published on this website as well. For more information, please see documentation
The FigShare service for University of Auckland, New Zealand was launched in January 2015 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item recieves a Digital Object identifier (DOI), which allows the data to be cited. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
San Raffaele Open Research Data Repository (ORDR) is an institutional platform which allows to safely store, preserve and share research data. ORDR is endowed with the essential characteristics of trusted repositories, as it ensures: a) open or restricted access to contents, with persistent unique identifiers to enable referencing and citation; b) a comprehensive set of Metadata fields to enable discovery and reuse; c) provisions to safeguard integrity, authenticity and long-term preservation of deposited data.
<<<!!!<<< The pages were merged. Please use "Forschungsdaten- und Servicezentrum der Bundesbank" https://www.re3data.org/repository/r3d100012252 >>>!!!<<<
The National Trauma Data BankĀ® (NTDB) is the largest aggregation of trauma registry data ever assembled. The goal of the NTDB is to inform the medical community, the public, and decision makers about a wide variety of issues that characterize the current state of care for injured persons. Registry data that is collected from the NTDB is compiled annually and disseminated in the forms of hospital benchmark reports, data quality reports, and research data sets. Research data sets that can be used by researchers. To gain access to NTDB data, researchers must submit requests through our online application process
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The German General Social Survey (ALLBUS) collects up-to-date data on attitudes, behavior, and social structure in Germany. Every two years since 1980 a representative cross section of the population is surveyed using both constant and variable questions. The ALLBUS data become available to interested parties for research and teaching as soon as they are processed and documented.