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Integrating heterogeneous rules-engine technologies with caGrid.

Joel H Saltz1, Scott Oster, Shannon L Hastings

  • 1The Ohio State University, Department of Biomedical Informatics, Columbus, OH, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|August 13, 2008
PubMed
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This study reviews rules-engine technologies and proposes an architectural model for integrating diverse rule engines with caGrid, addressing limitations of Business Process Execution Language (BPEL) in cancer research computing. The findings aim to enhance flexible rule execution within the National Cancer Institute

Area of Science:

  • Computational biology
  • Bioinformatics
  • Health informatics

Background:

  • Rules-engines are utilized across computational and biomedical fields.
  • The National Cancer Institute's (NCI) caBIG program has employed Business Process Execution Language (BPEL) for grid-based workflow orchestration.
  • Concerns exist regarding BPEL's suitability for broader rule definition and execution tasks within caBIG.

Purpose of the Study:

  • To evaluate the current landscape of rules-engine technologies.
  • To address the limitations of BPEL for diverse rule execution scenarios within caBIG.
  • To propose a novel architectural model for integrating heterogeneous rules-engines with caGrid.

Main Methods:

  • A comprehensive review of existing rules-engine technologies was conducted.

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  • An architectural model was formulated based on the review findings.
  • The model focuses on enabling the integration of diverse rules-engines with the caGrid infrastructure.

    • Main Results:

    • The review identified various rules-engine technologies and their capabilities.
    • An architectural model was developed to facilitate the integration of heterogeneous rules-engines.
    • The proposed model offers a solution for scenarios where BPEL may not be optimal.

    Conclusions:

    • The study provides a framework for integrating different rules-engines into caGrid.
    • This approach addresses the need for more flexible rule definition and execution in biomedical computing.
    • The proposed architecture supports the evolution of caBIG's computational infrastructure.