A graph showing the relationships between datasets and science domains
Diagram showing the science domains and projects supported by SciServer (click for a larger view).

SciServer comprises several scientific projects that have made their full datasets available in a common format and through a common set of interfaces. Many other projects will soon make their data available here as well.

The diagram shows SciServer’s projects, both those that currently make their datasets available through the SciServer environment and those that will in the future. Green ellipses mark specific projects, and red circles show those project’s databases. Blue ellipses map out which science domains these projects address. Click on the diagram for a larger view.

The list below gives the science domains addressed by SciServer’s current and future projects. Click on any of the icons for more information about that domain.

We also maintain a growing list of SciServer publications.

A graphic showing a view of a magnifying glass with soil organisms inside, surrounded by buildings, forests, and the GLUSEEN acronym

Soil Ecology

Like other field sciences, soil ecology research requires detailed and consistent monitoring of natural conditions. The more researchers can monitor natural environments, the more they can discover - but long-term widespread studies…

Oceanography

SciServer hosts numerical model output of high-resolution Ocean General Circulation Models (GCMs) set up and run by the research group of Prof. Thomas W. N. Haine (Johns Hopkins University - Department of…

Genomics

Recent advances in sequencing technology have led to an explosive growth in the amount of publicly available human sequence data. This represents an invaluable opportunity for scientific exploration and discovery, but the…

Materials Science

The MEDE Data Science Cloud: SciServer Based Data Science for Materials Scientists and Engineers At Hopkins we’ve developed the Materials in Extreme Dynamic Environments Data Science Cloud (MEDE-DSC) to address the need…

Turbulence

Turbulent fluid flow impacts a wide variety of engineering problems, but turbulence is mathematically complicated and poorly understood. One of the most productive research techniques is numerical simulation, but simulations powerful enough…
SDSS logo: a purple spectroscopic plate with the Big Dipper and Southern Cross

Astronomy

New tools for understanding our universe

Cosmological Physics

Another important application of large numerical simulations is in cosmological N-body simulations, which model the evolution of the Milky Way or the entire Universe. By 2016, SciServer will host several of these…