Data-driven material exploration is a ground-breaking research style; however, daily experimental results are difficult to record, analyze, and share. We report a data platform that losslessly describes the relationships of structures, properties, and processes as graphs in electronic laboratory notebooks. As a model project, organic superionic glassy conductors were explored by recording over 500 different experiments. Automated data analysis revealed the essential factors for a remarkable room temperature ionic conductivity of 10⁻⁴–10⁻³ S cm⁻¹ and a Li⁺ transference number of around 0.8. In contrast to previous materials research, everyone can access all the experimental results, including graphs, raw measurement data, and data processing systems, at a public repository. Direct data sharing will improve scientific communication and accelerate integration of material knowledge.

数据驱动的材料探索是一种开创性的研究方式；然而，日常实验结果难以记录、分析和分享。我们报告了一个数据平台，它在电子实验室笔记本中将结构、属性和过程的关系无损地描述为图形。作为一个模型项目，通过记录 500 多个不同的实验来探索有机超离子玻璃导体。自动数据分析揭示了 10 ^-4 –10 ^-3 S cm ^-1的显着室温离子电导率和 Li ⁺转移数约为0.8。与以前的材料研究相比，每个人都可以在公共存储库中访问所有实验结果，包括图表、原始测量数据和数据处理系统。直接数据共享将改善科学交流并加速材料知识的整合。