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Found 46 result(s)
The Wolfram Data Repository is a public resource that hosts an expanding collection of computable datasets, curated and structured to be suitable for immediate use in computation, visualization, analysis and more. Building on the Wolfram Data Framework and the Wolfram Language, the Wolfram Data Repository provides a uniform system for storing data and making it immediately computable and useful. With datasets of many types and from many sources, the Wolfram Data Repository is built to be a global resource for public data and data-backed publication.
The GSA Data Repository is an open file in which authors of articles in our journals can place information that supplements and expands on their article. These supplements will not appear in print but may be obtained from GSA.
<<<!!!<<< This record is merged into Continental Scientific Drilling Facility https://www.re3data.org/repository/r3d100012874 >>>!!!>>> LacCore curates cores and samples from continental coring and drilling expeditions around the world, and also archives metadata and contact information for cores stored at other institutions.LacCore curates cores and samples from continental coring and drilling expeditions around the world, and also archives metadata and contact information for cores stored at other institutions.
Teesside University Research Data Repository links to the University's Research Portal and enables your datasets to be linked to your staff profile. It helps prevent data loss by storing it in a safe secure environment and enables your research data to be open access. https://researchdata.tees.ac.uk/about.
The Rolling Deck to Repository (R2R) Program provides a comprehensive shore-side data management program for a suite of routine underway geophysical, water column, and atmospheric sensor data collected on vessels of the academic research fleet. R2R also ensures data are submitted to the NOAA National Centers for Environmental Information for long-term preservation.
Additionally to the institutional repository, current St. Edward's faculty have the option of uploading their work directly to their own SEU accounts on stedwards.figshare.com. Projects created on Figshare will automatically be published on this website as well. For more information, please see documentation
Chempound is a new generation repository architecture based on RDF, semantic dictionaries and linked data. It has been developed to hold any type of chemical object expressible in CML and is exemplified by crystallographic experiments and computational chemistry calculations. In both examples, the repository can hold >50k entries which can be searched by SPARQL endpoints and pre-indexing of key fields. The Chempound architecture is general and adaptable to other fields of data-rich science. The Chempound software is hosted at http://bitbucket.org/chempound and is available under the Apache License, Version 2.0
DNASU is a central repository for plasmid clones and collections. Currently we store and distribute over 200,000 plasmids including 75,000 human and mouse plasmids, full genome collections, the protein expression plasmids from the Protein Structure Initiative as the PSI: Biology Material Repository (PSI : Biology-MR), and both small and large collections from individual researchers. We are also a founding member and distributor of the ORFeome Collaboration plasmid collection.
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The Institutional Repository of the Universidad Santo Tomás manages, preserves, stores, disseminates and provides access to digital objects, the product of all academic and administrative production.
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Jülich DATA is a registry service to index all research data created at or in the context of Forschungszentrum Jülich. As an institutionial repository, it may also be used for data and software publications.
The FigShare service for University of Auckland, New Zealand was launched in January 2015 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item recieves a Digital Object identifier (DOI), which allows the data to be cited. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
The Million Song Dataset is a freely-available collection of audio features and metadata for a million contemporary popular music tracks. The core of the dataset is the feature analysis and metadata for one million songs, provided by The Echo Nest. The dataset does not include any audio, only the derived features. Note, however, that sample audio can be fetched from services like 7digital, using code we provide.
The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.
San Raffaele Open Research Data Repository (ORDR) is an institutional platform which allows to safely store, preserve and share research data. ORDR is endowed with the essential characteristics of trusted repositories, as it ensures: a) open or restricted access to contents, with persistent unique identifiers to enable referencing and citation; b) a comprehensive set of Metadata fields to enable discovery and reuse; c) provisions to safeguard integrity, authenticity and long-term preservation of deposited data.
As 3D and reality capture strategies for heritage documentation become more widespread and available, there has emerged a growing need to assist with guiding and facilitating accessibility to data, while maintaining scientific rigor, cultural and ethical sensitivity, discoverability, and archival standards. In response to these areas of need, The Open Heritage 3D Alliance (OHA) has developed as an advisory group governing the Open Heritage 3D initiative. This collaborative advisory group are among some of the earliest adopters of 3D heritage documentation technologies, and offer first-hand guidance for best practices in data management, sharing, and dissemination approaches for 3D cultural heritage projects. The founding members of the OHA, consist of experts and organizational leaders from CyArk, Historic Environment Scotland, and the University of South Florida Libraries, who together have significant repositories of legacy and on-going 3D research and documentation projects. These groups offer unique insight into not only the best practices for 3D data capture and sharing, but also have come together around concerns dealing with standards, formats, approach, ethics, and archive commitment. Together, the OHA has begun the journey to provide open access to cultural heritage 3D data, while maintaining integrity, security, and standards relating to discoverable dissemination. Together, the OHA will work to provide democratized access to primary heritage 3D data submitted from donors and organizations, and will help to facilitate an operation platform, archive, and organization of resources into the future.
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.