Collaborative Research: Automating Scaling and Data Processing in a Network of Sensors: Towards a Global Network for Lake Metabolism Research and Education

这项为期三年的合作项目由加州大学圣地亚哥分校、威斯康星大学麦迪逊分校和印第安纳大学共同完成，旨在实现数据生成网络的可扩展性和可扩展性自动化。网络基础设施和传感器网络的快速发展和部署为生态系统及其在全球环境过程中的作用的新知识创造了机会。扩大现有的网络和发展新的网络，以解决区域到全球尺度的湖泊代谢等重要生态过程的空间和时间变化问题，将需要在将数据从传感器传输到数据库、允许对传感器进行动态控制和重新配置网络、解决数据质量保证问题的架构方面进行新的技术改进。提供对网络中的分布式数据以及其他相关数据集的数据访问和查询，并提供分析工具。具体来说，这个项目有两个主要的技术目标：1。开发新的方法和工具，以帮助自动更新从动态部署的传感器到可公开访问的生物数据库的数据流。开发一套新的算法和软件，用于分析生物信息，根据传感器和数据库的数据自动检测（实时）事件，并应用于生物或物理事件或传感器故障的信号分类，从而实现快速响应。传播所开发的分析工具和框架将有助于现有的研究项目、不断发展的环境观测系统，如国家生态观测网、网络、机构、国际伙伴和K-16教师。研究生和本科生将参与该项目。该项目的软件工具和基础研究数据将被纳入现有的和正在进行的教师专业发展资源和6-12年级学生的教学资源。

This three-year award is a collaborative project by the University of California-San Diego, University of Wisconsin-Madison, and Indiana University to automate the extensibility and scalability of data-generating networks. Rapid advances and deployment of cyberinfrastructure and sensor networks have created opportunities for new knowledge of ecological systems and their role in global environmental processes. Expanding current networks and developing new networks capable of addressing the spatial and temporal variability of important ecological processes such as lake metabolism at regional to global scales will require novel technical improvements in an architecture that transports data from sensors to databases, allows dynamic control of sensors and reconfiguration of the network, addresses data quality assurance, provides data access and query to distributed data in the network as well as to other relevant datasets, and provides tools for analysis. Specifically this project has two major technical goals:1. Develop new methods and tools to help automate the updating of data flows from dynamically deployed sensors to publicly accessible biological databases.2. Develop a suite of new algorithms and software for analysis of biological information to automate detection (real-time) of events based on data from sensors and databases, with applications to classification of signals to biological or physical events or to sensor failure, allowing rapid response.The dissemination of analytical tools and framework developed will be useful to existing research projects, evolving environmental observing systems such as National Ecological Observatory Network, networks, agencies, international partners, and K-16 teachers. Graduate and under graduate students will participate in the project. Both software tools and basic research data from this project will be incorporated into existing and ongoing professional development resources for teachers and instructional resources for students in grades 6-12.