The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data increases the likelihood of reuse, and the potential of answering novel research questions. Ontologies are a useful tool for semantically tagging datasets as adding relevant metadata increases the understanding of how data was produced and increases its interoperability. Ontologies provide concepts for a particular domain as well as the relationships between concepts. By tagging data with ontology terms, data becomes both human and machine interpretable, allowing for increased reuse and interoperability. However, the task of identifying ontologies relevant to a particular research domain or technology is challenging, especially within the diverse realm of fundamental plant research. In this review, we outline the ontologies most relevant to the fundamental plant sciences and how they can be used to annotate data related to plant-specific experiments within metadata frameworks, such as Investigation-Study-Assay (ISA). We also outline repositories and platforms most useful for identifying applicable ontologies or finding ontology terms.

翻译：提升研究数据FAIR化（可发现性、可访问性、互操作性、可重用性）的重要性毋庸置疑，尤其面对当前组学技术产生的大规模复杂数据集时。促进数据集与其他类型数据的整合能增加其被重用的可能性，并有望回答新的研究问题。本体论作为对数据集进行语义标注的有力工具，通过添加相关元数据可增强对数据产生过程的理解并提升互操作性。本体论既提供特定领域的概念体系，也阐明概念间的关联关系。通过使用本体术语标注数据，数据同时具备人类可读与机器可解释性，从而提升重用与互操作能力。然而，识别特定研究领域或技术相关的本体论具有挑战性，这在基础植物研究的多元领域中尤为突出。本综述梳理了与基础植物科学最相关的本体论，并阐述如何利用其在元数据框架（如Investigation-Study-Assay, ISA）中对植物特异性实验数据进行注释。同时本文还列举了最适用于查找本体论与本体术语的存储库与平台。