Knowledge representation for digital publishing workflow
Digital Publishing involves printing processes where the film and plate making stages are eliminated. Digital printing is a process prone to error and subject to trial and experimentation; therefore resources such as ink, paper, and time are wasted before a top-quality output job is obtained. To fully exploit the potential of Digital Publishing flexible workflows are needed to provide services comparable to traditional publishing, but with the value added by the digital technology. Decision-making in such complex settings is highly dependent on human expertise. Knowledge engineering can play an important role in representing critical knowledge and performing inferences for decision-making that can lead to the development of knowledge-based system for automated workflow management. A framework for decision-making in workflow management is developed. This framework consists of an ontology combined with a ruled based system. The ontology contains a model for digital publishing while the ruled based provides mechanisms for inferences on this model. A set of rules for a digital publishing workflow for a print shop with three types of printers was tested with three critical printing job scenarios. Tests showed the validity of the approach with accurate problem diagnosis, recommendation for proper solution and explanations in all the scenarios. The framework is flexible and can be customized for other print shops settings and other job scenarios.