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Found 689 result(s)
The Coronavirus Antiviral Research Database is designed to expedite the development of SARS-CoV-2 antiviral therapy. It will benefit global coronavirus drug development efforts by (1) promoting uniform reporting of experimental results to facilitate comparisons between different candidate antiviral compounds; (2) identifying gaps in coronavirus antiviral drug development research; (3) helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development; (4) providing an objective, evidenced-based, source of information for the public; and (5) creating a hub for the exchange of ideas among coronavirus researchers whose feedback is sought and welcomed. By comprehensively reviewing all published laboratory, animal model, and clinical data on potential coronavirus therapies, the Database makes it unlikely that promising treatment approaches will be overlooked. In addition, by making it possible to compare the underlying data associated with competing treatment strategies, stakeholders will be better positioned to prioritize the most promising anti-coronavirus compounds for further development.
COW seeks to facilitate the collection, dissemination, and use of accurate and reliable quantitative data in international relations. Key principles of the project include a commitment to standard scientific principles of replication, data reliability, documentation, review, and the transparency of data collection procedures. More specifically, we are committed to the free public release of data sets to the research community, to release data in a timely manner after data collection is completed, to provide version numbers for data set and replication tracking, to provide appropriate dataset documentation, and to attempt to update, document, and distribute follow-on versions of datasets where possible. We intend to use our website as the center of our data distribution efforts, to serve as central site for collection of possible error information and questions, to provide a forum for interaction with users of Correlates of War data, and as a way for the international relations community to contribute to the continuing development of the project.
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The CosmoSim database provides results from cosmological simulations performed within different projects: the MultiDark and Bolshoi project, and the CLUES project. The CosmoSim webpage provides access to several cosmological simulations, with a separate database for each simulation. Simulations overview: https://www.cosmosim.org/cms/simulations/simulations-overview/ . CosmoSim is a contribution to the German Astrophysical Virtual Observatory.
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The COSYNA observatory measures key physical, sedimentary, geochemical and biological parameters at high temporal resolution in the water column and at the sediment and atmospheric boundaries. COSYNA delivers spatial representation through a set of fixed and moving platforms, like tidal flats poles, FerryBoxes, gliders, ship surveys, towed devices, remote sensing, etc.. New technologies like underwater nodes, benthic landers and automated sensors for water biogeochemical parameters are further developed and tested. A great variety of parameters is measured and processed, stored, analyzed, assimilated into models and visualized.
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Research Data and E-publishing repository of the Specialised Information Services Asia” (FID Asien), hosted by the East Asia Department of the Staatsbibliothek zu Berlin , was funded by the German Research Foundation (DFG)
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The CyberCell database (CCDB) is a comprehensive collection of detailed enzymatic, biological, chemical, genetic, and molecular biological data about E. coli (strain K12, MG1655). It is intended to provide sufficient information and querying capacity for biologists and computer scientists to use computers or detailed mathematical models to simulate all or part of a bacterial cell at a nanoscopic (10-9 m), mesoscopic (10-8 m).The CyberCell database CCDB actually consists of 4 browsable databases: 1) the main CyberCell database (CCDB - containing gene and protein information), 2) the 3D structure database (CC3D – containing information for structural proteomics), 3) the RNA database (CCRD – containing tRNA and rRNA information), and 4) the metabolite database (CCMD – containing metabolite information). Each of these databases is accessible through hyperlinked buttons located at the top of the CCDB homepage. All CCDB sub-databases are fully web enabled, permitting a wide variety of interactive browsing, search and display operations. and microscopic (10-6 m) level.
The aim of the project is systematic mapping of Czech and other languages in comparison with Czech. CNC corpora are accessible to everybody interested in studying the language after free registration.
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DABAR (Digital Academic Archives and Repositories) is the key component of the Croatian e-infrastructure’s data layer. It provides technological solutions that facilitate maintenance of higher education and science institutions' digital assets, i.e., various digital objects produced by the institutions and their employees.
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A domain-specific repository for the Life Sciences, covering the health, medical as well as the green life sciences. The repository services are primarily aimed at the Netherlands, but not exclusively.
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DaRUS, the data repository of the University of Stuttgart, offers a secure location for research data and codes, be it for the administration of own data, for exchange within a research group, for sharing with selected partners or for publishing.
<<<!!!<<< Stated 2019-10-30: Dash is no longer available. Researchers are advised to store their research data at Dryad https://www.re3data.org/repository/r3d100000044 >>>!!!>>> Dash is an open data publication platform for upload, access, and re-use of research data. Submissions to Dash may be from researchers at participating UC campuses, researchers in earth science and ecology (DataONE), and researchers submitting to the UC Press journals Elementa and Collabra. Self-service depositing of research data through Dash fulfills publisher, funder, and data management plan requirements regarding data sharing and preservation. When researchers publish their datasets through Dash, their datasets are issued a DOI (DataCite) to optimize citability, and are publicly available for download and re-use under a CC BY 4.0 or CC-0 license. Deposited data are preserved in Merritt, California Digital Library’s preservation repository.
The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH) is a centralized resource that allows researchers to share and access de-identified data from studies funded by NICHD. DASH also serves as a portal for requesting biospecimens from selected DASH studies.
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Research on German and European financial markets suffers from a lack of pan-European data sets. Also, existing sets do not provide a standard identification of, for example, companies. Therefore, researchers often utilize data from the United States where the integration of different databases is more advanced. As a consequence, empirical analyses are mostly based on non-European data. Because of the institutional differences, political recommendations that result from these analyses cannot – or only in a limited scope – be transferred to Europe. Against this background, the SAFE Research Data Center not only draws on the usual international data sources but also creates new European data sets, brings existing data together and processes them. The aim is to place the central research areas of SAFE on a common European data footing. Data access is provided by 'SAFE data sources' https://datacenter.safefrankfurt.de/datacenter/_databases/ and 'FiF - Repositorium für Forschungsdaten aus dem Finanzbereich (Preview version)' https://fif.safe-frankfurt.de/xmlui/
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INRAE is the world’s first organisation specialized on agricultural, food and environmental sciences. Data INRAE is offered by INRAE as part of its mission to open the results of its research. Data INRAE will share research data in relation with food, nutrition, agriculture and environment. It includes experimental, simulation and observation data, omic data, survey and text data. Only data produced by or in collaboration with INRAE will be hosted in the repository, but anyone can access the metadata and the open data.
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Data Publication Server Forschungszentrum Juelich is a web server for providing large data sets to the general public. It's main application is publishing data belonging to scientific publications.
Open access repository for digital research created at the University of Minnesota. U of M researchers may deposit data to the Libraries’ Data Repository for U of M (DRUM), subject to our collection policies. All data is publicly accessible. Data sets submitted to the Data Repository are reviewed by data curation staff to ensure that data is in a format and structure that best facilitates long-term access, discovery, and reuse.
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data.public.lu is Luxembourg's central and official platform for data from the public sector, from research institutes and the private sector.
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Launched in February 2020, data.sciencespo is a repository that offers visibility, sharing and preservation of data collected, curated and processed at Sciences Po. The repository is based on the Dataverse open-source software and organised into collections: CDSP Collection This collection managed by the Centre des données socio-politiques (CDSP) includes the catalogue of surveys, in the social science and humanities, processed and curated by CDSP engineers since 2005. This catalogue brings together surveys produced at Sciences Po and other French and international institutions. - Sciences Po collection (self-deposit) This collection, which is managed by the Direction des ressources et de l'information scientifique (DRIS), is intended to host data produced by researchers affiliated with Sciences Po, following the self-deposit process assisted by the Library's staff.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
The DRH is a quantitative and qualitative encyclopedia of religious history. It consists of a variety of entry types including religious group and religious place. Scholars contribute entries on their area of expertise by answering questions in standardised polls. Answers are initially coded in the binary format Yes/No or categorically, with comment boxes for qualitative comments, references and links. Experts are able to answer both Yes and No to the same question, enabling nuanced answers for specific circumstances. Media, such as photos, can also be attached to either individual questions or whole entries. The DRH captures scholarly disagreement, through fine-grained records and multiple temporally and spatially overlapping entries. Users can visualise changes in answers to questions over time and the extent of scholarly consensus or disagreement.