Translating the Science of Measuring Ecosystems at a National Scale: Developing NEON’s Online Learning Portal

Abstract:

“Big Data” are becoming increasingly common in many fields. The National Ecological Observatory Network (NEON) will be collecting data over the 30 years, using consistent, standardized methods across the United States. These freely available new data provide an opportunity for increased understanding of continental- and global scale processes such as changes in vegetation structure and condition, biodiversity and landuse.

However, while “big data” are becoming more accessible and available, integrating big data into the university courses is challenging. New and potentially unfamiliar data types and associated processing methods, required to work with a growing diversity of available data, may warrant time and resources that present a barrier to classroom integration. Analysis of these big datasets may further present a challenge given large file sizes, and uncertainty regarding best methods to properly statistically summarize and analyze results. Finally, teaching resources, in the form of demonstrative illustrations, and other supporting media that might help teach key data concepts, take time to find and more time to develop. Available resources are often spread widely across multi-online spaces.

This presentation will overview the development of NEON’s collaborative University-focused online education portal. Portal content will include 1) videos and supporting graphics that explain key concepts related to NEON data products including collection methods, key metadata to consider and consideration of potential error and uncertainty surrounding data analysis; and 2) packaged “lab” activities that include supporting data to be used in an ecology, biology or earth science classroom. To facilitate broad use in classrooms, lab activities will take advantage of freely and commonly available processing tools, techniques and scripts. All NEON materials are being developed in collaboration with existing labs and organizations.