Given the rapidly evolving COVID-19 situation, the organizing committee of the structural diversity workshop has decided to go to a shorter virtual meeting format on May 18th and 19th from 1:00 PM - 5:00 PM EST and to postpone the in-person site meeting for a future date.
Please cancel all travel arrangements you have made for May 19-20th in Boulder, CO but reserve May 18th and 19th for the virtual workshop.
This workshop will provide an introduction to the basics of data access and data navigation: discovering and accessing data via the NEON data portal, accessing data via the neonUtilities R package, understanding the content and quality of the data downloaded, and performing common data merges and transformations. Basic familiarity with R is recommended for participation in the workshop.
How to make sense of complex observational datasets, such as collected by CHEESEHEAD, the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors? Could it be possible to bridge scale-mismatches such as between observations and models by jointly using spatial grids, continuous time series and discrete surveys? This workshop offers practical solutions through tutorials on accessing CHEESEHEAD data and using Environmental Response Functions (ERF) to combine multiple data sources for inference across observational and model perspectives!
This workshop introduces participants to NEON, teaches them how to access and work with NEON data, and allows them to interact with NEON science staff to get assistance working on the specific data products they are interested in using. The workshop includes hands-on, interactive instruction on how to access and work with NEON data, both through the NEON data portal and programmatically. This workshop will also feature one or more presentations by scientists who work with NEON data within their area of expertise.
In this workshop we will explore the breadth of NEON educational resources through the lens of remote learning, including our Tutorials, Teaching Modules, and Science Videos. We will also do some live hand-on programming in R to access and explore NEON data. The goals for this workshop are to increase your awareness of NEON resources (documents and staff!), understand the workflow for working with NEON data in R, and to highlight how each of these can fit into an online curriculum.
In this workshop we will provide an introduction to discovering, accessing and preparing a variety of NEON data for your research, primarily using R. We will also explore a variety of educational resources designed to help familiarize you with NEON data, including but not limited to Tutorials, Teaching Modules, and Science Videos.
This workshop introduces participants to NEON, teaches them how to access and work with NEON data, and allows them to interact with NEON science staff to get assistance working on the specific data products they are interested in using. The workshop includes hands-on, interactive instruction on how to access and work with NEON data, both through the NEON data portal and programmatically. This event is hosted by the University of North Carolina, Greensboro, and is open to all.
This workshop focuses on NEON biodiversity data collected from the over 80 NEON field sites. Instruction will include an overview of the breadth of NEON biodiversity data before providing code-along instruction on how to get NEON biodiversity data into standardized formats (long and wide species tables with relevant metadata to make cross data product comparisons possible).
NEON Domain 17 field staff will be holding an Explore NEON workshop October 24th-25th. This 2-Day workshop will introduce participants to NEON as an organization and provide background on Domain 17 and the NEON sampling design. Participants will interact with Domain 17 field staff and members of the NEON Science team while learning how to view, download, and analyze NEON data using the popular coding environment R.
Join us for an intensive three-day, hands-on, remote workshop and learn how to create, use, deploy, and share analyses of NEON AOP data using the CyVerse platform.
