This paper elucidates the challenges and opportunities inherent in integrating data-driven methodologies into geotechnics, drawing inspiration from the success of materials informatics. Highlighting the intricacies of soil complexity, heterogeneity, and the lack of comprehensive data, the discussion underscores the pressing need for community-driven database initiatives and open science movements. By leveraging the transformative power of deep learning, particularly in feature extraction from high-dimensional data and the potential of transfer learning, we envision a paradigm shift towards a more collaborative and innovative geotechnics field. The paper concludes with a forward-looking stance, emphasizing the revolutionary potential brought about by advanced computational tools like large language models in reshaping geotechnics informatics.

翻译：本文借鉴材料信息学的成功经验，阐明了将数据驱动方法融入岩土工程领域所面临的挑战与机遇。通过突出土的复杂性、异质性以及缺乏全面数据等核心问题，讨论强调了建立社区驱动数据库和开放科学运动的迫切需求。借助深度学习变革性力量（尤其是高维数据特征提取能力与迁移学习潜力），我们预见到岩土工程领域将朝向更具协作性和创新性的范式转变。本文以前瞻性视角作结，强调大型语言模型等先进计算工具在重塑岩土信息学中的革命性潜力。