Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, non-standardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at its origin. LinkML documentation and code are available at linkml.io.

翻译：科学研究依赖于结构良好、标准化的数据；然而，大量数据存储在自由文本实验记录、非标准化电子表格或数据仓库等格式中。这种结构性的缺失对互操作性构成挑战，使得数据集成、验证和重用变得困难。LinkML（关联数据建模语言）是一个开放框架，可简化数据编写、验证和共享的过程。LinkML能够描述从基于列表的扁平模型到利用多态性和复合继承的复杂、互相关联且规范化的模型等一系列数据结构。它提供了一种易于使用的语法，不依赖于任何单一技术架构，并能与许多现有框架无缝集成。LinkML语法提供了一种描述模式、类别和关系的标准方法，使建模者能够构建定义明确、稳定且可选地与本体对齐的数据结构。一旦定义完成，LinkML模式可被导入到其他LinkML模式中。这些关键特性使LinkML成为跨学科合作的可访问平台，以及定义和共享数据语义的可靠方式。LinkML有助于减少异构性、复杂性和一次性数据模型的激增，同时支持符合FAIR数据标准。LinkML已在多个领域得到日益广泛的应用，包括生物学、化学、生物医学、微生物组研究、金融、电气工程、交通运输和商业软件开发。简而言之，LinkML使隐式模型变得显式可计算，并允许数据在源头实现标准化。LinkML文档和代码可在 linkml.io 获取。