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Found 23 result(s)
Museum explorers travel to ocean depths, the peaks of the Andes, Africa's Rift Valley, the rainforests of South America, and the deserts of Central Asia. Perhaps even to a field site or research institution in your own state, territory or country. In each area, researchers collect specimens: fossils, minerals, and rocks, plants and animals, tools and artworks. Collections care professionals have meticulously preserved, labeled, cataloged, and organized items of this kind for more than 150 years. Taken together, the NMNH collections form the largest, most comprehensive natural history collection in the world. By comparing items gathered in different eras and regions, scientists learn how our world has varied across time and space.
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KU Leuven RDR (pronounced "RaDaR") is KU Leuven's Research Data Repository, built on Dataverse.org - open source repository software built by Harvard University. RDR gives KU Leuven researchers a one-stop platform to upload, describe, and share their research data, conveniently and with support from university staff.
EBRAINS offers one of the most comprehensive platforms for sharing brain research data ranging in type as well as spatial and temporal scale. We provide the guidance and tools needed to overcome the hurdles associated with sharing data. The EBRAINS data curation service ensures that your dataset will be shared with maximum impact, visibility, reusability, and longevity, hhttps://www.ebrains.eu/data/find-data/. Find data - the user interface of the EBRAINS Knowledge Graph - allows you to easily find data of interest. EBRAINS hosts a wide range of data types and models from different species. All data are well described and can be accessed immediately for further analysis.
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.
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nmrXiv is an open, FAIR and consensus-driven NMR spectroscopy data repository and analysis platform. We archive raw and processed NMR data, providing support for browsing, search, analysis, and dissemination of NMR data worldwide.
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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.
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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AusGeochem is an easy-to-use platform for uploading, visualising, analysing and discovering georeferenced sample information and data produced by various geoscience research institutions such as universities, geological survey agencies and museums. With respect to analytical research laboratories, AusGeochem provides a centralised repository allowing laboratories to upload, archive, disseminate and publish their datasets. The intuitive user interface (UI) allows users to access national publicly funded data quickly through the ability to view an area of interest, synthesise a variety of geochemical data in real-time, and extract the required data, gaining novel scientific insights through multi-method data collation. Lithodat Pty Ltd has integrated built-in data synthesis functions into the platform, such as cumulative age histograms, age vs elevation plots, and step-heating diagrams, allowing for rapid inter-study comparisons. Data can be extracted in multiple formats for re-use in a variety of software systems, allowing for the integration of regional datasets into machine learning and AI systems.
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The Goethe University Data Repository (GUDe) provides a platform for its members to electronically archive, share, and publish their research data. GUDe is jointly operated by the University Library and the University Data Center of the Goethe University. The metadata of all public content is freely available and indexed by search engines as well as scientific web services. GUDe follows the FAIR principles for long-term accessibility (minimum 10 years), allows for reliable citation via DOIs as well as cooperative access to non-public data and operates on DSpace-CRIS v7. If you have any questions regarding the use of GUDe, please consult the user documentation.
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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.
The CZO Multiscale TROPIcal CatchmentS (M-TROPICS) consists in the merging, in 2016, of two previously-existing CZOs: BVET (India and Cameroon) and MSEC (Laos and Vietnam). The CZO Multiscale TROPIcal CatchmentS (M-TROPICS) provides the international scientific community with unique decennial time series of meteorological, hydrological, geochemical, and ecological variables in tropical environments. The CZO M-TROPICS involves academic and governmental partners in tropical countries (Cameroun, India, Lao PDR, and Vietnam) and is included in the Research Infrastructure OZCAR, the French contribution to the international CZO initiative.
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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.
OpenTopography facilitates community access to high-resolution, Earth science-oriented, topography data, and related tools and resources. The OpenTopography Facility is based at the San Diego Supercomputer Center at the University of California, San Diego and is operated in collaboration with colleagues in the School of Earth and Space Exploration at Arizona State University and Earthscope Consortium. Core operational support for OpenTopography comes from the National Science Foundation Earth Sciences.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
The online digital research data repository of multi-disciplinary research datasets produced at the University of Nottingham, hosted by Information Services and managed and curated by Libraries, Research & Learning Resources. University of Nottingham researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset.
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Rīga Stradiņš University (RSU) Dataverse is created for RSU researchers to deposit their data there after the end of research projects or other research activities, especially in cases when there are no trusted field specific repositories.
CORD is Cranfield University's research data repository, for secure preservation of institutional research data outputs. Cranfield is an exclusively postgraduate university that is a global leader for transformational research in technology and management. We are focused on the specialist themes of aerospace, defence and security, energy and power, environment and agrifood, manufacturing, transport systems, and water. The Cranfield School of Management is world leader in management education and research.
The Maine Dataverse Network is a cloud-based data repository intended to act as a long-term archive and to facilitate data sharing among the research community in accordance with NSF, NIH, NASA and other granting authority data management plan requirements. The Maine Dataverse Network offers a convenient and secure method of sharing and archiving data and is made available to the Maine research community at no cost.