The National Ecological Observatory Network (NEON) is a long-term ecological observatory focused on collecting and providing open, continental-scale data that characterize and quantify complex and rapidly changing ecological patterns and processes. The observatory provides over 180 different data products that cover a wide range of variables of interest to researchers across the ecological community. NEON creates and provides code and tools to enhance researchers’ ability to work with these data. In addition, NEON provides several platforms to help connect researchers sharing open code related to NEON data products with those who are also interested in using them.
Results/Conclusions
Code and tools created by NEON scientists are distributed through the NEONScience GitHub organization (https://github.com/NEONScience). Current tools include the neonUtilities R package that provides basic tools for accessing and working with most NEON data products, as well as the geoNEON package that facilitates access to NEON spatial data. Other code packages allow users to work with specific data products, including the eddy4R package that contains the algorithms used to create the Bundled eddy-covariance data product. Other code packages are designed to build upon existing NEON data products to create more user-friendly data for the ecological community. Current packages include those to calculate dissolved gas concentrations from air and equilibrated water data, calculate reaeration rates, and calculate nitrogen transformation rates from soil nitrogen content measurements. In addition, members of the ecological community are creating open code resources that use NEON data. NEON provides several platforms to help connect researchers sharing their code with those interested in using it. These include the Community Code section on the NEON Science website (https://www.neonscience.org/resources/code-resources) and the NEON Community platform (https://community.neonscience.org/) where researchers can share information about their code and analyses.