AutomationML Library Space: A concept for sharing and versioning Engineering Data Models

The digital transformation in engineering requires standardized information models to close gaps in digital value chains and to increase engineering efficiency. Despite the existence of several digital data models for engineering, their reuse is hindered by a lack of robust, guided mechanisms for sustainable development and publication. While the IT sector widely leverages Git-based workflows for sharing and collaborative software development, engineering data modelers have yet to adopt similar practices effectively. Our requirements and gap analysis reveals that, while services like Microsoft GitHub offers a robust starting point for collaborative and efficient modeling, more specialized mechanisms are required to effectively adapt Git-like workflows to the unique needs of engineering models. In response, we propose a novel method and an implementation that combines the capabilities of GitHub’s open-source collaboration strengths with engineering-specific enhancements as versioning and flexible deployment across both open and closed platforms. Interested readers are invited to explore and test the presented solution.