Name
Abstract | ||
|---|---|---|
As AI developers increasingly look to workflow technologies to perform complex integrations of individual software components, there is a growing need for the workflow systems to have expressive descriptions of those components. They must know more than just the types of a component's inputs and outputs; instead, they need detailed characterizations that allow them to make fine-grained distinctions between candidate components and between candidate workflows. This paper describes ProCat , an implemented ontology-based catalog for components, conceptualized as processes , that captures and communicates this detailed information. ProCat is built on a layered representation that allows reasoning about processes at varying levels of abstraction, from qualitative constraints reflecting preconditions and effects, to quantitative predictions about output data and performance. ProCat employs Semantic Web technologies RDF, OWL, and SPARQL, and builds on Semantic Web services research. We describe ProCat's approach to representing and answering queries about processes, discuss some early experiments evaluating the quantitative predictions, and report on our experience using ProCat in a system producing workflows for intelligence analysis. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-88564-1_54 | International Semantic Web Conference |
Keywords | Field | DocType |
ai developer,candidate workflows,semantic web services research,process catalog,detailed information,workflow system,semantic web technology,complex integration,workflow generation,detailed characterization,quantitative prediction,candidate component,intelligence analysis,software component | Ontology,Data mining,World Wide Web,Abstraction,Computer science,Semantic Web,SPARQL,Component-based software engineering,Workflow,RDF,Database,Intelligence analysis | Conference |
Volume | ISSN | Citations |
5318 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Wolverton | 1 | 264 | 28.16 |
| David Martin | 2 | 1355 | 165.44 |
| Ian Harrison | 3 | 1 | 1.04 |
| Jerome Thomere | 4 | 1 | 1.04 |