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Found 7 result(s)

HilData

HILDEonline

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HilData is registered by Hildesheim University Library, The access is via registration to the data and to the repository. Research data is with regards to educational science. Research data are sensitive and cannot be made fully open. HILDE Online is integrated in HilData: https://www.uni-hildesheim.de/celeb/projekte/fallarchiv-hilde/hildeonline-streaming-server/ HilData is working on its metadata (exposing metadata via interfaces) w.r.t. the FAIR principles and data citation. HilData and HILDE Online provide long-term storage and access to research data. The research data repository provides restricted access to its data. The research data repository uses DOI to make its provided data persistent, unique and citable.

NanoCommons Knowledge Base

NanoSolveIT Knowledge Base

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The NanoTox Knowlege Base provides access to Nanomaterials, their physico-chemical characterisations, toxicological assays and environmental data as well as computational model based descriptors.

BIH / Charité Virtual Research Environment

Berlin Institute of Health / Charité Virtual Research Environment

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The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.

Coscine

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Coscine is a web-based RDM platform for all kind of generic research data that was developed at RWTH Aachen University. It enables the storage, management and archiving for ten years of research and metadata generated in the context of research projects. The platform also promotes cooperation across organizational boundaries, as researchers can log in either via their organization via SSO or via ORCID. To enable meaningful metadata management for all research areas, Coscine allows flexible description with metadata based on established technologies (SHACL/RDF). The platform is designed to make warm/used/active data FAIR.

TOAR Surface Observation Database

TOAR Surface Stations Database

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The Tropospheric Ozone Assessment Report (TOAR) database of global surface observations is the world's most extensive collection of surface ozone measurements and includes also data on other air pollutants and on weather for some regions. Measurements from 1970 to 2019 (Version 1) have been collected in a relational database, and are made available via a graphical web interface, a REST service (https://toar-data.fz-juelich.de/api/v1) and as aggregated products on PANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.876108). Measurements from 1970 to present (Version 2) are being collected in a relational database, and are made available via a REST service (https://toar-data.fz-juelich.de/api/v2).

Kadi4Mat

Kadi4Mat instance KIT+

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Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. Kadi4Mat is the Karlsruhe Data Infrastructure for Materials Science, an open source software for managing research data. It is being developed as part of several research projects at the Institute for Applied Materials - Microstructure Modelling and Simulation (IAM-MMS) of the Karlsruhe Institute of Technology (KIT). The goal of this project is to combine the ability to manage and exchange data, the repository , with the possibility to analyze, visualize and transform said data, the electronic lab notebook (ELN). Kadi4Mat supports a close cooperation between experimenters, theorists and simulators, especially in materials science, to enable the acquisition of new knowledge and the development of novel materials. This is made possible by employing a modular and generic architecture, which allows to cover the specific needs of different scientists, each utilizing unique workflows. At the same time, this opens up the possibility of covering other research disciplines as well.

GISAID

GISAID EpiFlu database

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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.