By Topic

PWMDS: A system supporting provenance-based matching and discovery of workflows in proteomics data analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Guangmeng Zhai ; School of Computer Science, Fudan University, Shanghai, China ; Tun Lu ; Xing Huang ; Zhaocan Chen
more authors

Provenance plays a fundamental role in e-science to keep track of the data processing execution, evaluate the data quality, reproduce the analysis results, and especially share and re-use workflows. How to take full advantage of provenance to help scientists discover, match and select scientific workflows is a challenging work. Although some studies have been done to model, store, and query scientific workflows, little is done to build practical systems to support workflow matching and discovery. In this paper, we devise and implement a Provenance-Based Workflow Matching and Discovery System (PWMDS) for task-based pipelines in a proteomics data analysis platform called CoPExplorer to address the above challenge. With the proposed novel provenance model and workflow matching & discovery algorithms, PWMDS can provide scientists a ranked list of suitable service candidates for their specified workflows, and initial experiments demonstrate its effectiveness.

Published in:

Computer Supported Cooperative Work in Design (CSCWD), 2012 IEEE 16th International Conference on

Date of Conference:

23-25 May 2012