Data collection is an integral part of any citizen science project. Given the wide variety of projects, some level of expertise or, alternatively, some guidance for novice participants can greatly improve the quality of the collected data. A significant portion of citizen science projects depends on visual data, where photos or videos of different subjects are needed. Often these visual data are collected from all over the world, including remote locations. In this article, we introduce an authoring platform for easily creating mobile apps for citizen science projects that are empowered with client-side machine learning (ML) guidance. The apps created with our platform can help participants recognize the correct data and increase the efficiency of the data collection process. We demonstrate the application of our proposed platform with two use cases: a rip current detection app for a planned pilot study and a detection app for biodiversity-related projects.
翻译:数据收集是任何公民科学项目的一个组成部分。鉴于项目种类繁多,具有一定的专业知识,或者为新参与者提供一些指导,可以大大提高所收集的数据的质量。公民科学项目中有很大一部分依赖于视觉数据,需要不同主题的照片或视频。这些视觉数据通常来自世界各地,包括偏远地点。在本篇文章中,我们引入一个作者平台,方便为公民科学项目创建移动应用软件,这些应用软件具有客户-侧机学习(ML)指导的权能。用我们的平台创建的应用程序可以帮助参与者识别正确的数据,提高数据收集过程的效率。我们用两个使用案例展示了我们提议的平台的应用:一个用于计划试点研究的实时探测应用软件,一个用于生物多样性相关项目的探测应用软件。