About AWS Open Data Sponsorship Program
This program exists to help people discover and share data sets that are available by using AWS resources. Unless specifically stated in the applicable data set documentation, data sets available through the Registry of Open Data on AWS are not provided or maintained by AWS. Data sets are provided and maintained by a variety of third parties under a variety of licenses. Please check data set licenses and related documentation to determine if a data set may be used for you application. If you have a project using a listed data set please tell us about it at opendata@amazon.com.
AWS Open Data Sponsorship Program
AWS Open Data Sponsorship Program Products (319)
showing 311 - 319
Free | Publicly available
This bucket contains multiple datasets (as Quilt packages) created by the Allen Institute for Cell Science. The types of data included in this bucket are listed below: 1) Field of view or cropped images of cells 2) Segmentations of structures in the images (e.g., boundaries of cells, DNA, other intracellular structures, etc.) 3) Processed versions of the above images and segmentations 4) Machine learning predictions and labels of the data listed above 5) Models trained on the previously listed data 6) Additional supporting non-image data related to the above listed data types (e.g., gene expression data, whole genome sequencing data, features derived from the images or model predictions, metadata) 7) Simulation, analysis, and visualization data of in silico cell structures, cells, and cell populations External funding: The generation of some datasets was supported by the National Human Genome Research Institute of the National Institutes under Award Number UM1HG011593. The cont[...]
Free | Publicly available
The Genome Ark hosts genomic information for the Vertebrate Genomes Project (VGP) and other related projects. The VGP is an international collaboration that aims to generate complete and near error-free reference genomes for all extant vertebrate species. These genomes will be used to address fundamental questions in biology and disease, to identify species most genetically at risk for extinction, and to preserve genetic information of life.
Free | Publicly available
The New Zealand Elevation dataset consists of New Zealand's publicly owned digital elevation models and digital surface models, which are freely available to use under an open licence. The dataset contains 1m resolution grids derived from LiDAR data. Point clouds are not included in the initial release. All of the elevation files are Cloud Optimised GeoTIFFs using LERC compression for the main grid and LERC compression with lower maxzerror for the overviews. These elevation files are accompanied by STAC metadata. The elevation data is organised by region and survey.
Free | Publicly available
The Hubble Space Telescope (HST) is one of the most productive scientific instruments ever created. This dataset contains calibrated and raw data for all currently active instruments on HST: ACS, COS, STIS, WFC3, and FGS.
Free | Publicly available
The Multimedia Commons is a collection of audio and visual features computed for the nearly 100 million Creative Commons-licensed Flickr images and videos in the YFCC100M dataset from Yahoo! Labs, along with ground-truth annotations for selected subsets. The International Computer Science Institute (ICSI) and Lawrence Livermore National Laboratory are producing and distributing a core set of derived feature sets and annotations as part of an effort to enable large-scale video search capabilities. They have released this feature corpus into the public domain, under Creative Commons License 0, so it is free for anyone to use for any purpose.
Free | Publicly available
A multi-ancestry analysis of 7,221 phenotypes using a generalized mixed model association testing framework, spanning 16,119 genome-wide association studies. We provide standard meta-analysis across all populations and with a leave-one-population-out approach for each trait. The data are provided in tsv format (per phenotype) and Hail MatrixTable (all phenotypes and variants). Metadata is provided in phenotype and variant manifests.
Free | Publicly available
This dataset includes sequencing data, assemblies, and analyses for the offspring of ten parent-offspring trios.
Free | Publicly available
CCKP provides open access to a comprehensive suite of climate and climate change resources derived from the latest generation of climate data archives. Products are based on a consistent and transparent approach with a systematic way of pre-processing the raw observed and model-based projection data to enable inter-comparable use across a broad range of applications. Climate products consist of basic climate variables as well as a large collection (70+) of more specialized, application-orientated variables and indices across different scenarios. Precomputed data can be extracted per specified variables, select timeframes, climate projection scenarios, across ensembles or individual models, etc. CCKP adheres to data distributions standards defined under the Coupled Model Intercomparison Project (CMIP) and its contributions to the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports and latest scientific methodologies identified by the World Meteorological Organizatio[...]
Free | Publicly available
The NIH-funded Human Microbiome Project (HMP) is a collaborative effort of over 300 scientists from more than 80 organizations to comprehensively characterize the microbial communities inhabiting the human body and elucidate their role in human health and disease. To accomplish this task, microbial community samples were isolated from a cohort of 300 healthy adult human subjects at 18 specific sites within five regions of the body (oral cavity, airways, urogenital track, skin, and gut). Targeted sequencing of the 16S bacterial marker gene and/or whole metagenome shotgun sequencing was performed for thousands of these samples. In addition, whole genome sequences were generated for isolate strains collected from human body sites to act as reference organisms for analysis. Finally, 16S marker and whole metagenome sequencing was also done on additional samples from people suffering from several disease conditions.
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