Basic system process flow for SHEAF

Data access and code for SHEAF are organized using the Socio-Environmental Synthesis Center’s infrastructure.  All access to services are from this web site.  In some instances, you will need a login to get access.  If you are a member of the SHEAF team and you do not have a login, please email the team leadership, or use our contact page to request access.  Your communication will be followed up with a personal email or phone to confirm/validate your identity.

SESYNC and SHEAF Data Access Mechanisms
  • SHEAF Data Management Instructional Manual
    • The SHEAF Data Management Instructional Manual provides step-by-step information on how to access, upload, and analyze data.
  • Secure Data File Access
    • File server access to data on SESYNC servers: navigate to and login using your SESYNC credentials
    • You should use urls from these data in your RStudio code running on SESYNC.  Or download a dataset and use it locally
  • Secure Rstudio Server
    • Use your SESYNC credentials to access RStudio Server.  As noted above, you should use urls from the SESYNC file server in any code running on this remote RStudio/R server
  • R Shiny Server (web framework used to expose R model analysis – allowing for a ‘point and click’ approach to running a pre-developed model and review results)
    • We currently are running prototype shiny applications on servers at the University of Idaho.  We are transitioning to SESYNC servers
  • Github repository for code management (We use an organizational GitLab instance that is managed by SESYNC)
    • Our Gitlab code repos are located at: Use your SESYNC credentials to access.  You should be familiar with the Github mechanisms of pushing/pulling/cloning repos in order to use code from these repos.  You can also download a piece of code to run locally, you just won’t be able to push changes back to the server (which may be preferable if you are just exploring)
  • Interactive Python/Jupyter notebooks for python interaction.  While R is used for model development for sohcres, python is used as an integrative language for data wrangling and other gluing things together as needed
    • SESYNC has a BETA python notebook server –  You can access using your SESYNC credentials.  We currently do not have any python code loaded, but this server can be a mechanism to share python code for future modeling runs if needed.
  • ESRI StoryMAPS.  ESRI’s cloud-based story maps engine is used to present our findings and to allow for a more visual representation of data and derived knowledge.
  • BETA Data Analysis and SEM Dashboards.  R – based dashboard that allows for dynamic data interaction of project datasets. R – based dashboard that allows users to step thru a SEM analysis with initially-collected data.  This approach is BETA, and we absolutely understand that this model and approach is iterative and will change given feedback from our workshops.