A Process Catalog for Workflow Generation

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.