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Found 57 result(s)
DASS-BiH (Data Archive for Social Sciences in Bosnia and Herzegovina) is the national service whose role is to ensure long-term preservation and dissemination of social science research data. The purpose of the data archive is to provide a vital research data resource for researchers, teachers, students, and all other interested users.
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.
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.
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, https://ebrains.eu/services/data-knowledge/share-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.
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.
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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.
The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary cancer by providing electronic access to: Information on endogenous spontaneous and induced tumors in mice, including tumor frequency & latency data, Information on genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice) in which tumors arise, Information on genetic factors associated with tumor susceptibility in mice and somatic genetic-mutations observed in the tumors, Tumor pathology reports and images, References, supporting MTB data and Links to other online resources for cancer.
MIDRC aims to develop a high-quality repository for medical images related to COVID-19 and associated clinical data, and develop and foster medical image-based artificial intelligence (AI) for use in the detection, diagnosis, prognosis, and monitoring of COVID-19.
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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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Borealis, the Canadian Dataverse Repository, is a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. Borealis supports open discovery, management, sharing, and preservation of Canadian research data. Borealis is available to researchers who are affiliated with a participating Canadian university or research organization and their collaborators. Borealis is a shared service provided in partnership with Canadian regional academic library consortia, institutions, research organizations, and the Digital Research Alliance of Canada, with technical infrastructure hosted by Scholars Portal and the University of Toronto Libraries.
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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.
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IDSC is IZA's organizational unit whose purpose is to serve the scientific and infrastructural computing needs of IZA and its affiliated communities. IDSC is dedicated to supporting all users of data from the novice researcher to the experienced data analyst. IDSC aims at becoming the place for economically minded technologists and technologically savvy economists looking for data support, data access support and data services about labor economics. IDSC is actively involved in organizing events (see our next Red Cube Seminar Talk) for data professionals, data analysts, and scientific data users and young researchers to discuss and share findings and to establish contacts for future cooperation. All data collected are accessible to the scientific community as scientific use files for scholarly analyses free of charge. The Data Repository is available at https://datasets.iza.org/
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The repository KITopen is a key infrastructure service at KIT. Immediately KITopen not only allows the publication and archiving of publications, but also on research data from all disciplines and data types. The focus is on research data from publication projects that are specifically prepared for re-use.
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.