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.
