A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Kepler: An Extensible System for Design and Execution of Scientific Workflows
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Distributed computing with Triana on the Grid: Research Articles
Concurrency and Computation: Practice & Experience
Pegasus: A framework for mapping complex scientific workflows onto distributed systems
Scientific Programming
Process-Oriented Knowledge Support in a Clinical Research Setting
CBMS '07 Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems
Ontology-based data integration in data logistics workflows
ER'07 Proceedings of the 2007 conference on Advances in conceptual modeling: foundations and applications
Collection-Oriented scientific workflows for integrating and analyzing biological data
DILS'06 Proceedings of the Third international conference on Data Integration in the Life Sciences
Data Integration with the DaltOn Framework --- A Case Study
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
An ontology based approach to automating data integration in scientific workflows
Proceedings of the 7th International Conference on Frontiers of Information Technology
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In recent years, scientists are dealing more and more with data intensive and complex applications. Many scientific workflow systems emerged which adapt technology and methods stemming from the workflow management area and that should support scientists in understanding and working with their complex scenarios. However as these systems often descend from problem solving environments, many of them are missing a well structured conceptual method for process modeling and execution as a foundation. In this publication we present a comprehensive and well structured method for developing and analyzing process based scientific applications. This method is constituted by a process modeling framework, a data integration framework and a model driven approach to build up infrastructures for process modeling and execution.