ABI Development: Access, visualization, and statistical tools for the analysis of butterfly monitoring data

马里兰大学将蝴蝶监测小组网络以及信息学和统计学专家聚集在一起，开发一系列工具，以极大地扩大蝴蝶数据和知识的获取和使用。作为整个北美大陆蝴蝶监测项目网络的一部分，公民科学家进行了数千次调查，然而这些调查的数据却鲜为人知，因为缺乏：1)关于数据的知识和访问权限；2)可视化和共享这些关键数据集的工具；3)适当的分析模型。通过这个项目，将开发和推出几个新工具，包括一个用于大陆规模蝴蝶监测项目的网络界面和可视化工具，一个用于分发和可视化大型蝴蝶监测项目网络数据的框架，一个基于网络的物种特征数据库，以及一套用于分析最常见类型蝴蝶监测协议产生的数据的统计模型。所有的努力都将以开发广泛适用于蝴蝶监测项目以及其他昆虫监测项目的工具为目标，例如那些专注于蜻蜓、蟋蟀、瓢虫和蜜蜂的项目。设计的工具不仅对科学界和管理界有用，而且对蝴蝶监测数据的主要收集者——公众也有用。在整个项目中，本科生、研究生和博士后将参与各个阶段，以促进信息技术和统计分析方面的教育。

An award is made to the University of Maryland to bring together a network of butterfly monitoring groups and experts in both informatics and statistics to develop a series of tools to greatly expand the access and use of butterfly data and knowledge. Citizen-scientists throughout North America perform thousands of surveys as part of a continent-wide network of butterfly monitoring programs, yet data from these surveys, are little known due to a lack of: 1) knowledge about and access to the data, 2) tools to visualize and share these critical data sets, and 3) appropriate models for analysis. Through this project, several new tools will be developed and launched, including a web interface and visualization tool for a continental-scale butterfly monitoring program, a framework for the distribution and visualization for data emerging from a large network of butterfly monitoring programs, and a web-enabled database of species traits, and a suite of statistical models to analyze data resulting from the most common types of butterfly monitoring protocols. All efforts will be targeted toward developing tools that are broadly transferrable among butterfly monitoring programs as well as other insect monitoring programs, such as those focused on dragonflies, crickets, ladybeetles, and bees. Tools will be designed to be useful not just to the scientific and management communities, but also for the general public, the primary collectors of butterfly monitoring data. Throughout this project, undergraduates, graduates, and post-doctoral associates will be involved in all stages to foster education in information technology and statistical analysis.