Toward Metadata-Driven Experimentation in Software Engineering: A Vision for Reproducible, Interoperable, and Transparent Research

Empirical Software Engineering increasingly relies on controlled experimentation, yet current reproducibility practices focus primarily on artifact availability rather than on how experimental knowledge is represented and reused at scale. As a result, many experiments remain reproducible in principle but difficult to interpret, compare, and integrate across contexts and time. This position paper argues that this gap constitutes a structural challenge for the future of Software Engineering and proposes metadata-driven experimentation as an evolution of existing reproducibility practices, treating experimental metadata and conceptual structure as first-class research artifacts. By enabling structured, machine-interpretable representations of experimental intent, design, context, and analysis, metadata complements narrative reporting and executable artifacts, supporting cumulative knowledge building and scalable empirical research in the coming decade.