CDAT is a powerful and complete front-end to a rich set of visual-data exploration and analysis capabilities well suited for data analysis problems.
Welcome to CDAT!
New here? Don’t worry! We’ll help you get started. If you’re interested in what you can do with CDAT, you can take a look at our gallery. If you’re interested in anything you see there, you can look into getting our application installed.
We'll give you a hand.
Having trouble with something? We’ve got a great community of people who can give you a hand on our support email list.
We're on GitHub!
If you want to get to know us, you can come chat with us on our developer mail list. If you want to get up to speed with the project, our wiki is kept up-to-date with what you need to get going.
The CDAT Project
CDAT builds on the following key technologies:
The Community Data Analysis Tools (CDAT) framework developed at LLNL for the analysis, visualization, and management of large-scale distributed climate data;
ParaView: an open-source, multi-platform, parallel-capable visualization tool with recently added capabilities to better support specific needs of the climate-science community;
VisTrails, an open-source scientific workflow and provenance management system that supports data exploration and visualization;
VisIt: an open-source, parallel-capable, visual-data exploration and analysis tool that is capable of running on a diverse set of platforms, ranging from laptops to the Department of Energy's largest supercomputers.
These combined tools, along with others such as the R open-source statistical
analysis and plotting software and custom packages (e.g. vtDV3D), form CDAT
and provide a synergistic approach to climate modeling, allowing researchers to
advance scientific visualization of large-scale climate data sets. The CDAT
framework couples powerful software infrastructures through two primary means:
Tightly coupled integration of the CDAT Core with the VTK/ParaView infrastructure to provide high-performance, parallel-streaming data analysis and visualization of massive climate-data sets (other tighly coupled tools include
VCS, VisTrails, DV3D, and ESMF/ESMP);
Loosely coupled integration to provide the flexibility of using tools quickly
in the infrastructure such as ViSUS, VisIt, R, and MatLab for data analysis and
visualization as well as to apply customized data analysis applications within
an integrated environment.
Within both paradigms, CDAT will provide data-provenance capture and
mechanisms to support data analysis via the VisTrails infrastructure.