Zhang Limin, Starr Julian, Ford Bruce, Reznicek Anton, Zhou Yuxuan, Léveillé-Bourret Étienne, Lacroix-Carignan Étienne, Cayouette Jacques, Smith Tyler W, Sutherland Donald, Catling Paul, Saarela Jeffery M, Cui Hong, Macklin James
School of Information, University of Arizona, 1103 E. 2nd Street, Tucson, AZ 85719, USA.
School of Fine Arts, Huaiyin Normal University, 71 Jiaotong Road, Huaian, Jiangsu 223001, China.
Database (Oxford). 2025 Jan 29;2025. doi: 10.1093/database/baae097.
It is well-known that the use of vocabulary in phenotype treatments is often inconsistent. An earlier survey of biologists who create or use phenotypic characters revealed that this lack of standardization leads to ambiguities, frustrating both the consumers and producers of phenotypic data. Such ambiguities are challenging for biologists, and more so for Artificial Intelligence, to resolve. That survey also indicated a strong interest in a new authoring workflow supported by ontologies to ensure published phenotype data are FAIR (Findable, Accessible, Interoperable, and Reusable) and suitable for large-scale computational analyses. In this article, we introduce a prototype software system designed for authors to produce computational phenotype data. This platform includes a web-based, ontology-enhanced editor for taxonomic characters (Character Recorder), an Ontology Backend holding standardized vocabulary (the Cared Ontology), and a mobile application for resolving ontological conflicts (Conflict Resolver). We present two formal user evaluations of Character Recorder, the main interface authors would interact with to produce FAIR data. The evaluations were conducted with undergraduate biology students and Carex experts. We evaluated Character Recorder against Microsoft Excel on their effectiveness, efficiency, and the cognitive demands of the users in producing computable taxon-by-character matrices. The evaluations showed that Character Recorder is quickly learnable for both student and professional participants, with its cognitive demand comparable to Excel's. Participants agreed that the quality of the data Character Recorder yielded was superior. Students praised Character Recorder's educational value, while Carex experts were keen to recommend it and help evolve it from a prototype into a comprehensive tool. Feature improvements recommended by expert participants have been implemented after the evaluation.
众所周知，在表型处理中词汇的使用往往不一致。一项针对创建或使用表型特征的生物学家的早期调查显示，这种缺乏标准化的情况会导致歧义，令表型数据的使用者和生产者都感到沮丧。对于生物学家来说，解决这些歧义具有挑战性，而对于人工智能来说更是如此。该调查还表明，人们对由本体支持的新创作工作流程有着浓厚兴趣，以确保已发表的表型数据是FAIR的（可查找、可访问、可互操作和可重用），并适用于大规模计算分析。在本文中，我们介绍了一个为作者设计的用于生成计算表型数据的原型软件系统。这个平台包括一个基于网络的、用于分类特征的本体增强编辑器（特征记录器）、一个保存标准化词汇的本体后端（Cared本体）以及一个用于解决本体冲突的移动应用程序（冲突解决器）。我们对特征记录器进行了两次正式的用户评估，特征记录器是作者为生成FAIR数据而与之交互的主要界面。评估是与本科生物学学生和苔草专家进行的。我们将特征记录器与Microsoft Excel在生成可计算的分类单元-特征矩阵时的有效性、效率以及对用户的认知要求方面进行了评估。评估表明，特征记录器对于学生和专业参与者来说都很容易学习，其认知要求与Excel相当。参与者一致认为特征记录器生成的数据质量更高。学生们称赞了特征记录器的教育价值，而苔草专家则热衷于推荐它，并帮助将其从一个原型发展成为一个全面的工具。专家参与者建议的功能改进在评估后已经得到实施。
