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Found 324 result(s)
IDEALS is an institutional repository that collects, disseminates, and provides persistent and reliable access to the research and scholarship of faculty, staff, and students at the University of Illinois at Urbana-Champaign. Faculty, staff, graduate students, and in some cases undergraduate students, can deposit their research and scholarship directly into IDEALS. Departments can use IDEALS to distribute their working papers, technical reports, or other research material. Contact us at https://www.ideals.illinois.edu/feedback for more information.
Content type(s)
A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.
Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
The LJMU Research Data Repository is the University's institutional repository where researchers can safely deposit and store research data on an Open Access basis. Data stored in the LJMU Research Data Repository can be made freely available to anyone online and located by users of web search engines.
NKN is now Research Computing and Data Services (RCDS)! We provide data management support for UI researchers and their regional, national, and international collaborators. This support keeps researchers at the cutting-edge of science and increases our institution's competitiveness for external research grants. Quality data and metadata developed in research projects and curated by RCDS (formerly NKN) is a valuable, long-term asset upon which to develop and build new research and science.
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The Tropical Data Hub (TDH) Research Data repository makes data collections and datasets generated by James Cook University researchers searchable and accessible. This increases their visibility and facilitates sharing and collaboration both within JCU and externally. Services provided include archival storage, access controls (open access preferred), metadata review and DOI minting.
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.
CLARIN-LV is a national node of Clarin ERIC (Common Language Resources and Technology Infrastructure). The mission of the repository is to ensure the availability and long­ term preservation of language resources. The data stored in the repository are being actively used and cited in scientific publications.
>>>!!!<<< This repository is no longer available, pleas use DataON http://doi.org/10.17616/R31NJMV3 >>>!!!<<< Domestic and foreign research data information in one place It is a national research data portal.
The figshare service for The Open University was launched in 2016 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 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.
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The University of Victoria Dataverse is a research data repository for our faculty, researchers, and students. It is a general repository, suitable for all disciplines, and accepts a wide range of data types and formats. All deposited files are held in a secure environment on Canadian servers, and depositors can choose to make content available publicly, to specific individuals, or to keep it locked.
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depositar — taking the term from the Portuguese/Spanish verb for to deposit — is an online repository for research data. The site is built by the researchers for the researchers. You are free to deposit, discover, and reuse datasets on depositar for all your research purposes.
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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.
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Macquarie University's Institutional Research Data Repository (RDR) allows researchers to upload, publish, search and download research data. The RDR promotes collaboration, data sharing and discovery amongst researchers globally according to FAIR data principles. The RDR is based on Figshare for Institutions, which has been specifically tailored to suit the needs of the Macquarie University research community.
OLOS is a Swiss-based data management portal tailored for researchers and institutions. Powerful yet easy to use, OLOS works with most tools and formats across all scientific disciplines to help researchers safely manage, publish and preserve their data. The solution was developed as part of a larger project focusing on Data Life Cycle Management (dlcm.ch) that aims to develop various services for research data management. Thanks to its highly modular architecture, OLOS can be adapted both to small institutions that need a "turnkey" solution and to larger ones that can rely on OLOS to complement what they have already implemented. OLOS is compatible with all formats in use in the different scientific disciplines and is based on modern technology that interconnects with researchers' environments (such as Electronic Laboratory Notebooks or Laboratory Information Management Systems).
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BIRD is a digital service that collects, preserves, and distributes digital material. Repositories are important tools for preserving an organization's legacy; they facilitate digital preservation and scholarly communication.
>>>>>!!!<<<<< As of 01/12/2015, deposit of data on SLDR website will be suspended to allow the public opening of Ortolang platform https://www.ortolang.fr/#/market/home .>>>>>!!!<<<<<
The Research Data Center PIAAC (RDC PIAAC) has been accredited by the German Data Forum (RatSWD). The RDC PIAAC makes research data accessible to the scientific community and offers advice to the users. The RDC PIAAC provides German and international datasets in the educational field focusing on the adult population, especially on the Programme for the International Assessment of Adult Competencies (PIAAC).
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Tallinn University of Technology Data Repository (TalTechData) is a storage space for researchers to deposit data sets associated with their research. The main goal of TalTechData is to gather all fields of research data and encouraging open science and FAIR principles (Findable, Accessible, Interoperable and Reusable). Through preserving open research data TalTechData enriches academic quality and collaboration, supports innovative developments and supports overall use of scientific materials.
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The Digital Repository of Ireland (DRI) is a national trusted digital repository (TDR) for Ireland’s social and cultural data. We preserve, curate, and provide sustained access to a wealth of Ireland’s humanities and social sciences data through a single online portal. The repository houses unique and important collections from a variety of organisations including higher education institutions, cultural institutions, government agencies, and specialist archives. DRI has staff members from a wide variety of backgrounds, including software engineers, designers, digital archivists and librarians, data curators, policy and requirements specialists, educators, project managers, social scientists and humanities scholars. DRI is certified by the CoreTrustSeal, the current TDR standard widely recommended for best practice in Open Science. In addition to providing trusted digital repository services, the DRI is also Ireland’s research centre for best practices in digital archiving, repository infrastructures, preservation policy, research data management and advocacy at the national and European levels. DRI contributes to policy making nationally (e.g. via the National Open Research Forum and the IRC), and internationally, including European Commission expert groups, the DPC, RDA and the OECD.
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).