An Exercise in Concurrent Software Engineering: The MUSIC360 Digital Ecosystem

In complex digital business ecosystems like MUSIC360, practitioners develop various requirement perspectives concurrently and independently due to time constraints and time-to-market considerations, but by doing so also create alignment issues between these perspectives. We argue that a knowledge graph-based approach enables systematic analysis and reasoning about traceability between these perspectives: in our case, the business value model of the ecosystem, associated data models, and security requirement items. In the knowledge graph, the elements of the business value model (e.g., economic actors), data elements (e.g., data assets), and security requirement item elements (e.g. access controls) are nodes connected by edges representing semantic/logic relationships (e.g., protects, authorizes). We illustrate the use of the traceability knowledge graph using the EU MUSIC360 project. The resulting traceability knowledge graph allows us to identify the perspectives' incompleteness and inconsistency, analyze the causes, and derive suggestions for improving model and requirements quality while using concurrent engineering. Theoretically, we contribute a cross-perspective traceability framework that unifies value-oriented, data-oriented, and security-oriented requirement-related artefacts into a single semantic network, plus reusable traceability patterns and rules to guide early-phase alignment. Practically, we show how to embed traceability analysis into concurrent engineering to improve requirement quality without sacrificing speed.