Data

The NDS consortium provides access to a number of high-impact research datasets and repositories serving multiple disciplines. Many of these datasets are too large to fit in traditional models of research data access and discovery and must be access "in-place." NDS is working to streamline access to these and similar datasets through the vision of a DataDNS service.

Featured Datasets

MHD Turbulence in Core-Collapse Supernovae

A series of snapshots in time from four ultra-high resolution 3D magnetohydrodynamic simulations of rapidly rotating stellar core-collapse. The simulations were run on the Blue Waters supercomputer using the Einstein Toolkit. Dataset size: 201 TB.

Access

This dataset is currently available via Globus and Swift object storage at SDSC Cloud . Data DOI: http://dx.doi.org/doi:10.21970/N9RP4P .

Citation

Mösta, Phillip; Ott, Christian D.; Radice, David; Roberts, Luke F.; Schnetter, Erik; Haas, Roland, "A large-scale dynamo and magnetoturbulence in rapidly rottating core-collapse supernovae," 2015, http://dx.doi.org/10.1038/nature15755 .


National Bridge Inventory (NBI)

In collaboration with the Midwest Big Data Hub (MBDH) and researchers at the University of Nebraska, Omaha , NDS is hosting an instance of the National Bridge Inventory (NBI) dataset stored in a Mongo database for active analysis along with Jupyter notebooks demonstrating sample analysis. The NBI database widely used for bridge health and safey research.

Access

The NBI database and Jupyter environment are available via the Labs Workbench service.

See also

Bridging Big Data: Big Data Innovations for Bridge Health


TERRA Phenotyping Reference Platform (TERRA-REF)

The ARPA-E TERRA-REF project provides researchers with access to the reference phenotyping data and analytics resources using a high performance computing environment. The reference phenotyping data includes direct measurements and sensor observations, derived plant phenotypes, and genetic and genomic data. The data storage and compute pipeline are hosted on the ROGER system at the National Center for Supercomputing Applications (NCSA). The complete reference dataset is expected to be >2 PB.

Access

The TERRA-REF data is hosted on the ROGER system and available via Globus , Sensor Data Portal , and the Analysis Workbench.

See also

TERRA-REF Documentation


Renaissance Simulations

The results of the Renaissance Simulations, a suite of extremely high-resolution and physics-rich AMR calculations of high-redshift galaxy formation performed on the Blue Waters supercomputer using the Enzo toolkit. Dataset size: 90 TB.

Access

Data is avaiable via the Renaissance Simulations Laboratory and Swift object storage via SDSC Cloud .

Citation

Norman, B. W. O. and J. H. W. and H. X. and M. L. (2015). "Probing the Ultraviolet Luminosity Function of the Earliest Galaxies with the Renaissance Simulations." The Astrophysical Journal Letters, 807(1), L12.


Dark Sky Simulations

The cosmological N-body simulation designed to provide a quantitative and accessible model of the evolution of the large-scale Universe. Dataset size: 36 TB.

Access

Data is avaiable via yt.Hub .

See also

DarkSky Early Data Release

Citation

Warren, M. S., Friedland, A., Holz, D. E., Skillman, S. W., Sutter, P. M., Turk, M. J., & Wechsler, R. H. (2014). "Dark Sky Simulations Collaboration." Zenodo. https://doi.org/10.5281/zenodo.10777.


CARMA Archive

The Combined Array for Research in Millimeter Astronomy (CARMA) archive contains contain visibility data in custom binary formats, images in the standard FITS format, and auxiliary data in XML and ASCII text-file format. Dataset size: 43 TB.

Access

NDS is in the process of providing access to the datasets via Globus.


Featured Repositories

Materials Data Facility

The Materials Data Facility (MDF) provides access to research data for the materials science community.

Access

MDF data is available via Globus and the MDF repository .


Sustainable Environment through Actionable Data (SEAD)

Following the completion of NSF funding in June 2017, NDS continues to provide access to the SEAD data and tools.

Access

SEAD data is available via SEAD repository .