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Found 9 result(s)

Brain Image Library

BIL

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Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.

LDbase

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A research data repository for the education and developmental sciences.

DANDI

Distributed Archives for Neurophysiology Data Integration

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The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.

System for Earth Sample Registration

SESAR

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SESAR, the System for Earth Sample Registration, is a global registry for specimens (rocks, sediments, minerals, fossils, fluids, gas) and related sampling features from our natural environment. SESAR's objective is to overcome the problem of ambiguous sample naming in the Earth Sciences. SESAR maintains a database of sample records that are contributed by its users. Each sample that is registered with SESAR is assigned an International Geo Sample Number IGSN to ensure its global unique identification.

Pennsieve Discover

formerly: Blackfynn Discover

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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.

AuScope Data Repository

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The AuScope Data Repository preserves and offers continued access to data from Australia’s geoscience community working on fundamental geoscience questions and grand challenges, including climate change, natural resources security and natural hazards.

UC Irvine Machine Learning Repository

UCI Machine Learning Repository

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The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.

Marine Data Archive

MDA

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The Marine Data Archive (MDA) is an online repository specifically developed to independently archive data files in a fully documented manner. The MDA can serve individuals, consortia, working groups and institutes to manage data files and file versions for a specific context (project, report, analysis, monitoring campaign), as a personal or institutional archive or back-up system and as an open repository for data publication.

Materials Data Facility

MDF

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The Materials Data Facility (MDF) is set of data services built specifically to support materials science researchers. MDF consists of two synergistic services, data publication and data discovery (in development). The production-ready data publication service offers a scalable repository where materials scientists can publish, preserve, and share research data. The repository provides a focal point for the materials community, enabling publication and discovery of materials data of all sizes.