Enabling Content Management Systems as an Information Source in Model-driven Projects

2025-08-27

AI Summary

In highly customized scenarios, the information structure of headless CMSs is difficult to discover and model automatically, forcing practitioners to rely on error-prone, labor-intensive manual integration. Method: We propose a model-driven automation framework that, for the first time, enables automatic schema discovery, explicit metamodeling, and platform-agnostic middleware library generation for headless CMSs. Our approach integrates REST API semantic parsing with metamodel inference to construct a reusable middleware abstraction layer, supporting plug-and-play integration across multiple CMS platforms (e.g., Contentful, Strapi). Contribution/Results: An open-source implementation demonstrates that our framework significantly reduces human modeling error rates and cross-application integration costs, while improving both accuracy and efficiency in content interaction design.

Technology Category

• Data Mining & Knowledge Management: Semantic Web
• Planning, Routing, and Scheduling: Planning with Language Models
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Web Mining and Content Analysis: Web data integration and cleaning
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems

Abstract

Content Management Systems (CMSs) are the most popular tool when it comes to create and publish content across the web. Recently, CMSs have evolved, becoming emph{headless}. Content served by a emph{headless CMS} aims to be consumed by other applications and services through REST APIs rather than by human users through a web browser. This evolution has enabled CMSs to become a notorious source of content to be used in a variety of contexts beyond pure web navigation. As such, CMS have become an important component of many information systems. Unfortunately, we still lack the tools to properly discover and manage the information stored in a CMS, often highly customized to the needs of a specific domain. Currently, this is mostly a time-consuming and error-prone manual process. In this paper, we propose a model-based framework to facilitate the integration of headless CMSs in software development processes. Our framework is able to discover and explicitly represent the information schema behind the CMS. This facilitates designing the interaction between the CMS model and other components consuming that information. These interactions are then generated as part of a middleware library that offers platform-agnostic access to the CMS to all the client applications. The complete framework is open-source and available online.

Problem

• Integrating headless CMSs into model-driven software development processes
• Discovering and representing CMS information schema automatically
• Generating platform-agnostic middleware for CMS-client application interactions

Innovation

• Model-based framework for headless CMS integration
• Automated discovery of CMS information schema
• Middleware generation for platform-agnostic CMS access