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Found 18 result(s)
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Open At LaTrobe (OPAL) is La Trobe University’s official repository for Open Access materials generated by academic and professional staff and HDR students. These include publications and other research outputs, theses, open data, and educational resources. OPAL enables the storage, sharing, and selective publication of files and the assignment of a persistent DOI. Users maintain control over who can see their private files and all uploads are stored in La Trobe University approved storage. Access is via La Trobe University login credentials. La Trobe produces a wide range of useful datasets including supplementary data associated with publications and stand-alone datasets and collections.
>>>!!!<<< This site is going away on April 1, 2021. General access to the site has been disabled and community users will see an error upon login. >>>!!!<<< Socrata’s cloud-based solution allows government organizations to put their data online, make data-driven decisions, operate more efficiently, and share insights with citizens.
The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical state, variability and dynamics of the ocean and marine ecosystems for the global ocean and the European regional seas. The observations and forecasts produced by the service support all marine applications, including: Marine safety; Marine resources; Coastal and marine environment; Weather, seasonal forecasting and climate. For instance, the provision of data on currents, winds and sea ice help to improve ship routing services, offshore operations or search and rescue operations, thus contributing to marine safety. The service also contributes to the protection and the sustainable management of living marine resources in particular for aquaculture, sustainable fisheries management or regional fishery organisations decision-making process. Physical and marine biogeochemical components are useful for water quality monitoring and pollution control. Sea level rise is a key indicator of climate change and helps to assess coastal erosion. Sea surface temperature elevation has direct consequences on marine ecosystems and appearance of tropical cyclones. As a result of this, the service supports a wide range of coastal and marine environment applications. Many of the data delivered by the service (e.g. temperature, salinity, sea level, currents, wind and sea ice) also play a crucial role in the domain of weather, climate and seasonal forecasting.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
eLaborate is an online work environment in which scholars can upload scans, transcribe and annotate text, and publish the results as on online text edition which is freely available to all users. Short information about and a link to already published editions is presented on the page Editions under Published. Information about editions currently being prepared is posted on the page Ongoing projects. The eLaborate work environment for the creation and publication of online digital editions is developed by the Huygens Institute for the History of the Netherlands of the Royal Netherlands Academy of Arts and Sciences. Although the institute considers itself primarily a research facility and does not maintain a public collection profile, Huygens ING actively maintains almost 200 digitally available resource collections.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
myExperiment is a collaborative environment where scientists can safely publish their workflows and in silico experiments, share them with groups and find those of others. Workflows, other digital objects and bundles (called Packs) can now be swapped, sorted and searched like photos and videos on the Web. Unlike Facebook or MySpace, myExperiment fully understands the needs of the researcher and makes it really easy for the next generation of scientists to contribute to a pool of scientific methods, build communities and form relationships — reducing time-to-experiment, sharing expertise and avoiding reinvention. myExperiment is now the largest public repository of scientific workflows.
GWAS Central (previously the Human Genome Variation database of Genotype-to-Phenotype information) is a database of summary level findings from genetic association studies, both large and small. We actively gather datasets from public domain projects, and encourage direct data submission from the community.
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The Repository stores in digital format all the academic and scientific documentation (Theses, Articles, Papers) generated by the institution. Its main objectives are to promote open access to the scientific-technological production generated by the Institution. It is organized by collections: Thesis and Final Works, Research, Institutional History and Photographic Archive.
The aim of the Freshwater Biodiversity Data Portal is to integrate and provide open and free access to freshwater biodiversity data from all possible sources. To this end, we offer tools and support for scientists interested in documenting/advertising their dataset in the metadatabase, in submitting or publishing their primary biodiversity data (i.e. species occurrence records) or having their dataset linked to the Freshwater Biodiversity Data Portal. This information portal serves as a data discovery tool, and allows scientists and managers to complement, integrate, and analyse distribution data to elucidate patterns in freshwater biodiversity. The Freshwater Biodiversity Data Portal was initiated under the EU FP7 BioFresh project and continued through the Freshwater Information Platform (http://www.freshwaterplatform.eu). To ensure the broad availability of biodiversity data and integration in the global GBIF index, we strongly encourages scientists to submit any primary biodiversity data published in a scientific paper to national nodes of GBIF or to thematic initiatives such as the Freshwater Biodiversity Data Portal.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis. The PhysioNet resource has three closely interdependent components: An extensive archive ("PhysioBank"), a large and growing library of software ("PhysioToolkit"), and a collection of popular tutorials and educational materials
Data@Lincoln is the research data repository for Lincoln University (New Zealand). Datasets may stand alone, or may consist of appendices to theses, or figures or other supplementary material to journal articles and other publications.
InterPro collects information about protein sequence analysis and classification, providing access to a database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. Sequences in InterPro are classified at superfamily, family, and subfamily. InterPro predicts the occurrence of functional domains, repeats, and important sites, and adds in-depth annotation such as GO terms to the protein signatures.