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Open Tools for NEON Data: Lessons from Open Code Development by NEON Scientists and the NEON User Community
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  • Claire Lunch,
  • Christine Laney,
  • Megan Jones,
  • David Durden
Claire Lunch
National Ecological Observatory Network

Corresponding Author:[email protected]

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Christine Laney
Battelle
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Megan Jones
National Ecological Observatory Network - Battelle
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David Durden
National Ecological Observatory Network
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Abstract

An engaged community of scientific programmers is an invaluable asset to any open data provider. The National Ecological Observatory Network (NEON) is a long-term 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 earth and life sciences. 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. 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 contain the algorithms used to produce specific data products, including the eddy4R package, used to create the bundled eddy-covariance data product. Finally, some code packages are designed to build upon published NEON data to create value-added, derived products. Members of NEON’s user community have contributed to some of the packages described above, and others are creating their own open code resources for using NEON data. Use of NEON code packages and development of open code are highly variable within the NEON user community, and NEON has explored several approaches to engage users in this aspect of the observatory, including online tutorials, webinars, workshops, and hackathons. Developing and expanding an engaged community of open code users around NEON data is a continuing and evolving effort for the NEON project.