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Found 6 result(s)

WorldData.AI

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WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.

PAIN repository

Pain and Interoception Imaging Network Repository

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The PAIN Repository is a recently funded NIH initiative, which has two components: an archive for already collected imaging data (Archived Repository), and a repository for structural and functional brain images and metadata acquired prospectively using standardized acquisition parameters (Standardized Repository) in healthy control subjects and patients with different types of chronic pain. The PAIN Repository provides the infrastructure for storage of standardized resting state functional, diffusion tensor imaging and structural brain imaging data and associated biological, physiological and behavioral metadata from multiple scanning sites, and provides tools to facilitate analysis of the resulting comprehensive data sets.

TB Database

Tuberculosis Database

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The repository is no longer available. >>>!!!<<< 2018-08-29: no more access to TB Database >>>!!!<<<

VertNet

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VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.

TRY

Plant Trait Database

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This database is a global archive and describes plant traits from throughout the globe. TRY is a network of vegetation scientists headed by DIVERSITAS, IGBP, iDiv, the Max Planck Institute for Biogeochemistry and an international Advisory Board. About half of the data are geo-referenced, providing a global coverage of more than 8000 measurement sites.

Global Terrestrial Network for Permafrost

GTN-P Database

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The GTN-P database is an object-related database open for a diverse range of data. Because of the complexity of the PAGE21 project, data provided in the GTN-P management system are extremely diverse, ranging from active-layer thickness measurements once per year to flux measurement every second and everthing else in between. The data can be assigned to two broad categories: Quantitative data which is all data that can be measured numerically. Quantitative data comprise all in situ measurements, i.e. permafrost temperatures and active layer thickness (mechanical probing, frost/thaw tubes, soil temperature profiles). Qualitative data (knowledge products) are observations not based on measurements, such as observations on soils, vegetation, relief, etc.