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 Instructions 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 Github repos are located at:  These are our public repos that are kept in sync with our Gitlab repos.
    • Our Gitlab code repos are located at:  These are our repos that contain all of our public code, as well as any code that we want to restrict for public access. Use your SESYNC credentials to login.  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.