• Subscribe

iSGTW Feature - Kepler 1.0

Feature - Placing Kepler at the center of your computing system

A scientific workflow describes a series of structured computations that arise in scientific problem-solving. Typically a sequence of analysis tools are invoked in a routine manner. Workflows often include sequences of format translations that ensure that the tools can process each other's outputs, and perform routine verification and validation of the data and the outputs to ensure that the computation as a whole remains on track. (Adapted from Munindar P. Singh and Mladen A. Vouk )

The LiDAR workfow communicates both with the portal and the Grid layers (click for larger version showing layers ). This central workflow layer, controlled by the Kepler workfow manager, coordinates the multiple distributed Grid components in a single environment as a data analysis pipeline. It submits and monitors jobs onto the Grid, and handles third party transfer of derived intermediate products among consecutive compute clusters, as defned by the workfow description. In addition, it sends control information to the portal client about the overall execution of the process.

Image courtesy of LiDAR.

Scientists want to concentrate on science. They appreciate handy tools that simplify the process of analyzing data, especially when the data are stored in a complicated variety of systems and formats.

The open source Kepler workflow system, for which version 1.0 was just released, is just such a tool; it helps scientists from a wide range of disciplines design scientific workflows and execute them efficiently. Kepler's native support of parallel processing allows these workflows to leverage the compute power of grid technologies.

Kepler has attracted collaborators and users from ecology, molecular biology, genetics, physics, chemistry, conservation science, oceanography, hydrology, library science, and computer science. Scientists have adopted earlier Kepler versions to study the effect of climate change on species distribution, simulate supernova explosions, and perform complex statistical analyses.

Researchers from the National Center for Ecological Analysis and Synthesis (NCEAS) at UC Santa Barbara, the San Diego Supercomputer Center at UC San Diego, and the Science Environment for Ecological Knowledge (SEEK) and Scientific Data Management (SDM) projects at UC Davis founded the Kepler Project in 2002. Kepler extends Ptolemy II , a system developed at UC Berkeley for modeling, simulation and design of concurrent, real-time embedded systems .

Artificially illuminated digital elevation model derived from LiDAR data hosted by GEON and produced by the GEON LiDAR system which uses the Kepler workflow. The image, in greyscale, is rendered in Google Earth with some transparency to show fusion with the imagery. The location is a famous site on the San Andreas Fault in central California known as Wallace Creek where stream channels have been offset by repeated earthquakes. View is to the south, south-east.

Image courtesy of LiDAR

"We wanted to create an open, customizable, extensible and robust scientific workflow environment for solving scientific problems, and Kepler 1.0 realizes our goal," said Ilkay Altintas, lab director of the Scientific Workflow Automation Technologies (SWAT) group at SDSC. "It provides access to diverse technologies, and also furnishes a basis for many exciting features in the works."

Kepler 1.0 comes with a searchable library containing more than 350 ready-to-use processing components that can be customized and operated from a desktop environment to perform analysis, automate data management, and integrate applications efficiently.

-Anne Heavey

The Kepler project is funded through various grants from the National Science Foundation and the Department of Energy. To download the Kepler application or learn more about the project, see http://www.kepler-project.org

Join the conversation

Do you have story ideas or something to contribute? Let us know!

Copyright © 2021 Science Node ™  |  Privacy Notice  |  Sitemap

Disclaimer: While Science Node ™ does its best to provide complete and up-to-date information, it does not warrant that the information is error-free and disclaims all liability with respect to results from the use of the information.


We encourage you to republish this article online and in print, it’s free under our creative commons attribution license, but please follow some simple guidelines:
  1. You have to credit our authors.
  2. You have to credit ScienceNode.org — where possible include our logo with a link back to the original article.
  3. You can simply run the first few lines of the article and then add: “Read the full article on ScienceNode.org” containing a link back to the original article.
  4. The easiest way to get the article on your site is to embed the code below.