Sold by: IRSA
Open data
|
Deployed on AWS
This release consists of simulated data products designed to mimic observations of the same region of the sky as seen by two astronomical facilities: the Nancy Grace Roman Telescope and the Vera C. Rubin Observatory.
Overview
This release consists of simulated data products designed to mimic observations of the same region of the sky as seen by two astronomical facilities: the Nancy Grace Roman Telescope and the Vera C. Rubin Observatory.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- The simulated Roman data products include truth files listing the basic physical properties of the simulated astronomical objects; truth images that include the appropriate bandpass and PSF but limited sources of noise; calibrated images that include relevant backgrounds and major sources of noise; and coadded images created using the IMCOM software.
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::nasa-irsa-simulations/troxel2024/roman/
- AWS region
- us-east-1
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://nasa-irsa-simulations/troxel2024/roman//
- Description
- The simulated Rubin data products include raw pixel data, calibrated exposures, coadds of the calibrated exposures, and catalogs of photometry measured from the simulated images.
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::nasa-irsa-simulations/troxel2024/rubin/
- AWS region
- us-east-1
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://nasa-irsa-simulations/troxel2024/rubin//
Resources
Vendor resources
Support
Managed By
NASA/IPAC Infrared Science Archive (IRSA ) at Caltech
How to cite
OpenUniverse Matched Rubin and Roman Simulations: Data Preview (Troxel et al. 2024) was accessed on DATE from https://registry.opendata.aws/troxel2024 .
Similar products
This release consists of simulated data products designed to mimic observations of the same region of the sky as seen by two astronomical facilities: the Nancy Grace Roman Telescope and the Vera C. Rubin Observatory.
Pre-built refgenie reference genome data assets used for aligning and analyzing DNA sequence data.
This project primarily aims to facilitate performance benchmarking in robotics research. The dataset provides mesh models, RGB, RGB-D and point cloud images of over 80 objects. The physical objects are also available via the YCB benchmarking project. The data are collected by two state of the art systems: UC Berkley's scanning rig and the Google scanner. The UC Berkley's scanning rig data provide meshes generated with Poisson reconstruction, meshes generated with volumetric range image integration, textured versions of both meshes, Kinbody files for using the meshes with OpenRAVE, 600 High-resolution RGB images, 600 RGB-D images, and 600 point cloud images for each object. The Google scanner data provides 3 meshes with different resolutions (16k, 64k, and 512k polygons), textured versions of each mesh, Kinbody files for using the meshes with OpenRAVE.
This dataset captures Sunflower's genetic diversity originating
from thousands of wild, cultivated, and landrace sunflower
individuals distributed across North America.
The data consists of raw sequences and associated botanical metadata,
aligned sequences (to three different reference genomes), and sets of
SNPs computed across several cohorts.