Ontological Model of Factors of Prepress Processing of Newspaper and Magazine Publications

Abstract

The article addresses the problematics of prepress processing of newspaper and magazine publications, the quality of which directly determines both the perception of informational content and the overall quality of printed products. It has been established that individual component of this process — namely dimensional parameters, typographic, illustrative and compositional design, layout design, and typesetting — define the structural and functional characteristics of a publication. The lack of an integrated system for their formalized representation complicates the unification of terminology and creates obstacles to the automation of publishing workflows. An ontological model of prepress processing factors is proposed, providing a formalized representation of key parameters and their interrelations. The ontology implements a hierarchical structure of concepts and attributes reflecting the interaction among page dimensions, column organization, typographic solutions, illustrative materials, and compositional schemes. The principal classes of the developed ontology correspond to the factors influencing the quality of prepress processing of newspaper and magazine publications, each of which incorporates subclasses of the second level. This approach enables the creation of a coherent knowledge environment suitable for reuse, extension, and integration into contemporary publishing information systems. A methodology for quality assessment of prepress processing of newspaper and magazine publications is proposed, based on the developed ontology that determines the correspondence of factor parameters to recommended design standards and the integral quality indicator. A quality assessment algorithm for prepress processing of newspaper and magazine publications has been developed, which enables users to input layout parameters, aligns them with the respective ontology classes and properties, verifies compliance with normative thresholds, calculates the integral quality index, and generates recommendations for optimization