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Found 47 result(s)
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.
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PARADISEC (the Pacific And Regional Archive for Digital Sources in Endangered Cultures) offers a facility for digital conservation and access to endangered materials from all over the world. Our research group has developed models to ensure that the archive can provide access to interested communities, and conforms with emerging international standards for digital archiving. We have established a framework for accessioning, cataloguing and digitising audio, text and visual material, and preserving digital copies. The primary focus of this initial stage is safe preservation of material that would otherwise be lost, especially field tapes from the 1950s and 1960s.
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.
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The Marine Data Portal is a product of the “Underway”- Data initiative of the German Marine Research Alliance (Deutsche Allianz Meeresforschung - DAM) and is supported by the marine science centers AWI, GEOMAR and Hereon of the Helmholtz Association. This initiative aims to improve and standardize the systematic data collection and data evaluation for expeditions with German research vessels and marine observation. It supports scientists in their data management duties and fosters (data) science through FAIR and open access to marine research data. AWI, GEOMAR and Hereon develop this marine data hub (Marehub) to build a decentralized data infrastructure for processing, long-term archiving and dissemination of marine observation and model data and data products. The Marine Data Portal provides user-friendly, centralized access to marine research data, reports and publications from a wide range of data repositories and libraries in the context of German marine research and its international collaboration. The Marine Data Portal is developed by scientists for scientists in order to facilitate Findability and Access of marine research data for Reuse. It supports machine-readable and data driven science. Please note that the quality of the data may vary depending on the purpose for which it was originally collected.
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The Portuguese Archive of Social Information (APIS) is a scientific infrastructure acting on the domain of preservation and dissemination of social science data. Based at Instituto de Ciências Sociais, University of Lisbon, the archive works towards the acquisition and sharing of digital data for the purposes of public consultation, secondary analysis and pedagogical use. The archive comprises a range of datasets provided by research projects of the national scientific community.
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The Data Repository of the Department of Statistical Sciences of the University of Padova is a research data archive with the objective of sharing datasets collected within the Department. The service aims to facilitate data discovery, data sharing, and reuse.
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The GEOROC data repository hosts research data within the scope of the GEOROC database: geochemical compositions of rocks, glasses, minerals and inclusions from all geological settings on Earth. The repository is curated by the Digital Geochemical Data Infrastructure (DIGIS) project at Göttingen University.
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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 Federated Research Data Repository (FRDR) is a bilingual publishing platform for sharing and preserving Canadian research data. It is a curated, general-purpose repository, custom built for large datasets.
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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.
IAGOS aims to provide long-term, regular and spatially resolved in situ observations of the atmospheric composition. The observation systems are deployed on a fleet of 10 to 15 commercial aircraft measuring atmospheric chemistry concentrations and meteorological fields. The IAGOS Data Centre manages and gives access to all the data produced within the project.
RIVMdata is a metadata catalog. This catalog is filled with the metadata of RIVM datasets. ISO 19115 and DCAT standards are used as the metadata standards. The catalog consists of an internal site, which is only accessible to RIVM employees, and an external site, in which the metadata is accessible to the general public.
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The Austrian NeuroCloud (ANC) is a FAIR-enabling platform for sustainable research data management in Cognitive Neuroscience. Most of the offered research data is restricted, the publicly available datasets can be seen under https://data.anc.plus.ac.at/explore The ANC offers tools and services to archive, manage, and share neurocognitive data flexibly and according to community standards. Scientists have full control over what they share (e.g., full original datasets or data derivatives), how they share it (by choosing from a selection of licensing models), and with whom (e.g., by using the ANC’s adjustable User Agreement templates). The ANC provides persistent DOIs for data releases and operates in accordance with European GDPR. Moreover, the ANC fully supports the mission of the EOSC and is committed to the EU’s open science policy, legal standards, and best open science practices. Accordingly, the ANC aspires to facilitate FAIR data operations along the entire data lifecycle, actively supporting the ongoing shift in research culture towards increased transparency, data reusability, and result reproducibility.
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.
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Multidisciplinary research data repository, hosted by DTU, the Danish Technical University.
The U.S. Department of Energy’s (DOE) Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data archive serves Earth and environmental science data. ESS-DIVE is funded by the Data Management program within the Climate and Environmental Science Division under the DOE’s Office of Biological and Environmental Research program (BER), and is maintained by the Lawrence Berkeley National Laboratory. ESS-DIVE will archive and publicly share data obtained from observational, experimental, and modeling research that is funded by the DOE’s Office of Science under its Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) programs within the Environmental Systems Science (ESS) activity. ESS-DIVE was launched in July 2017, and is designed to provide long-term stewardship and use of data from observational, experimental and modeling activities in the DOE in the Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) Programs in the Environmental System Science (ESS) activity.
ISRIC - World Soil Information is an independent foundation. As regular member of the ICS World Data System it is also known as World Data Centre for Soils (WDC-Soils). ISRIC was founded in 1966 through the International Soil Science Society (ISSS) and United Nations Educational, Scientific and Cultural Organization (UNESCO), with a mission to "help to increase the availability and use of soil data, information and knowledge to enable better decision making for sustainable land management around the world". Our work is organised according to four work streams: 1) Global soil information & standards, 2) Community of practice for soil information providers, 3) Products and services to support SLM (sustainable land management) decision making, and 4) Awareness, education and dialogues. data.isric.org is our central location for searching and downloading soil data bases/maps from around the world. We support Open Data whenever possible, respecting inherited rights (licenses).
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.