Industrial symbiosis and carbon capture are increasingly recognized as critical strategies for reducing emissions and resource consumption in industrial parks. However, existing research remains fragmented across tools, methods, and case-specific applications, providing limited guidance for effective real-world deployment of data-driven approaches. This study addresses this gap through a PRISMA-guided scoping review of 116 publications, complemented by a targeted practitioner survey conducted within the IEA IETS Task 21 initiative to assess practical relevance and adoption challenges. The review identifies a broad landscape of data-driven tools, ranging from high-technology-readiness simulation and optimization platforms to emerging visualization and matchmaking solutions. While the literature demonstrates substantial methodological maturity, the combined evidence reveals a persistent gap between tool availability and effective implementation. Key barriers include fragmented and non-standardized data infrastructures, confidentiality constraints, limited stakeholder coordination, and weak policy and market incentives. Based on the integrated analysis of literature and practitioner insights, the paper proposes a conceptual framework that links tools and methods with data infrastructure, stakeholder governance, policy, and market enablers, and implementation contexts. The findings highlight that improving data governance, interoperability, and collaborative implementation pathways is as critical as advancing analytical capabilities. The study concludes by outlining focused directions for future research, including AI-enabled optimization, standardized data-sharing frameworks, and coordinated pilot projects to support scalable low-carbon industrial transformation.
Ma et al. (2026) studied this question.