Scalable Knowledge Discovery Through Grid Workflows

Abstract

The goal of this effort was to drastically reduce the human effort required to configure and execute new workflows for data analysis from weeks to minutes by eliminating the need for costly human monitoring and intervention. This involves developing end-to-end data analysis systems to analyze data from many different sources and with many different algorithms and analytical tools. Their approach combined three central ideas: 1) workflows with rich representations of algorithmic requirements and data products, 2) semantic representations to enable automatic generation of complex workflows, and 3) grid computing to manage the high performance of many workflows in distributed cross-organization environments.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2009
Accession Number
ADA498386

Entities

People

  • Ewa Deelman
  • Gaurang Mehta
  • Jihie Kim
  • Karan Vahi
  • Paul Groth
  • Varun Ratnakar
  • Yolanda Gil

Organizations

  • University of Southern California

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Artificial Intelligence
  • Automatic
  • Computer Programming
  • Computing System Architectures
  • Data Analysis
  • Data Mining
  • Data Sets
  • Databases
  • Detection
  • Information Science
  • Machine Learning
  • Ontologies
  • Operating Systems
  • Relational Database Management Systems
  • Websites

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development