From site science to network science: using cyberinfrastructure to translate lake sensor data into ecological knowledge

Synthesizing sensor data to conduct network science, i.e., science that transcends the boundaries of individual ecological observatories, is technologically, organizationally, and socially challenging.  One approach to address these obstacles is to employ cyberinfrastructure to integrate data, technology, and people from globally distributed sites into a collaborative network.  Working across scientific and administrative boundaries, we provide examples in which computing tools, models, and analytical techniques have been used to answer cutting-edge science questions with North Temperate Lakes (NTL) LTER and Global Lake Ecological Observatory Network (GLEON) data.  GLEON is a grassroots, international network of computer scientists, engineers, information technology specialists, and ecologists that collect and analyze lake sensor data to better understand water quality dynamics.  We demonstrate how the cyberinfrastructure approach enabled us to:

1. Quantify and characterize the full distribution of lakes at the continental scale
2. Determine the roles lakes play in processing landscape organic carbon
3. Reveal complex interactions among microbial communities through time
4. Determine the relative importance of wind-driven and convective forces in controlling gas efflux from lakes spanning six orders of magnitude in size. 

All of these projects merged a diverse array of sensor data as well as other data sources to develop ecological insight from complex datasets, highlighting the utility of cyber-tools to transform data into knowledge.  In addition, these projects emphasize the potential for cyberinfrastructure to connect sites into sensor networks in other ecosystems.