Achieving carbon neutrality by 2050 is a daunting global challenge. Exploring chemical space is thus becoming a crucial strategy to address this problem. Framework Materials (FMs), including Metal-Organic Frameworks (MOFs) and Metal-Organic Polyhedra (MOPs), are highly customizable solids formed from a wide variety of organic linkers and metal nodes, making them promising candidates for carbon-neutrality applications. However, optimizing their synthesis is often complex and labor-intensive due to the numerous variables involved and the lack of a definitive construction blueprint. We have adopted a data-driven approach that leverages structural databases and digitizes chemical intuition to streamline this process. This presentation will highlight examples of MOFs, emphasizing the role of chemical intuition and the necessity of data-driven strategies when faced with numerous variables. Despite the vast combination possibilities offered by MOFs, their optimization remains a formidable challenge, necessitating innovative solutions from both computational and synthetic chemists. I will also focus on case studies involving Zeolitic lmidazolate Frameworks (ZIFs), Zirconium-based MOFs, and MOPs, demonstrating how theoretical and experimental databases are instrumental in identifying synthetic targets and advancing FM discovery, particularly in the context of carbon neutrality. These digital repositories of chemical insights significantly accelerate the discovery and optimization of innovative FMs, providing crucial support for overcoming carbon-neutral challenges.