Data from: Crowdsourced geometric morphometrics enable rapid large-scale collection and analysis of phenotypic data

1. Advances in genomics and informatics have enabled the production of large phylogenetic trees. However, the ability to collect large phenotypic datasets has not kept pace. 2. Here, we present a method to quickly and accurately gather morphometric data using crowdsourced image-based landmarking. 3. We find that crowdsourced workers perform similarly to experienced morphologists on the same digitization tasks. We also demonstrate the speed and accuracy of our method on seven families of ray-finned fishes (Actinopterygii). 4. Crowdsourcing will enable the collection of morphological data across vast radiations of organisms, and can facilitate richer inference on the macroevolutionary processes that shape phenotypic diversity across the tree of life.

1. 基因组学与信息学的进步已推动大型系统发育树（phylogenetic tree）的构建，但大型表型数据集（phenotypic dataset）的采集能力却未能与之同步发展。
2. 本文提出一种基于众包图像地标标记的方法，可快速且精准地获取形态计量数据（morphometric data）。
3. 研究表明，在同类数字化任务中，众包工作者的表现与经验丰富的形态学家不相上下；此外，我们还在7个辐鳍鱼类（Actinopterygii）类群中验证了本方法的高效性与准确性。
4. 众包技术将助力覆盖各类生物辐射演化类群的形态数据采集，并能为解析塑造生命之树表型多样性的宏观进化（macroevolution）过程提供更丰富的推断依据。