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Kepler: An extensible system for design and execution of scientific workflows

A modeling and execution environment for distributed scientific workflows

A framework for the design and reuse of grid workflows

A web service composition and deployment framework for scientific workflows [abstract]

Evaluating predictive models of species' distributions: Criteria for selecting optimal models

Enabling knowledge-based software engineering through semantic object-relational mappings

Domain-specific conceptualizations are increasingly specified as formal ontologies, as part of ongoing efforts for enabling the semantic web. However, experience has shown that semantic models and their in-carnations into OWL structures, though powerful for expressing complex abstractions, remain difficult to utilize in conventional software projects. In this paper we present our work for coupling ontologies with conventional domain-centric data models and object-relational persistence.

Ontologies, javabeans and relational databases for enabling semantic linking

Knowledge-based software engineering enables a programmer to integrate rich semantics in the software development process. In this work, we show how an OWL/RDF knowledge base can be integrated with conventional domain-centric data models (enterprise Java beans) and object-relational mapping toolkits (Hibernate). We present a pathway for the software developer to generate enterprise Java beans source code and hibernate object-relational mappings starting from a domain ontology.

Incremental validation of xml documents

Accessing and using sensor data within the Kepler scientific workflow system

Incorporating semantics in scientific workflow authoring

The tools used to analyze scientific data are often distinct from those used to archive, retrieve, and query data. A scientific workflow environment, however, allows one to seamlessly combine these functions within the same application. This increase in capability is accompanied by an increase in complexity, especially in workflow tools like Kepler, which target multiple science domains including ecology, geology, oceanography, physics, and biology.