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
- Secure Data File Access
- File server access to data on SESYNC servers: navigate to http://files.sesync.org 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: https://gitlab.sesync.org/groups/soilsesfeedback. 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 – https://jupyter.sesync.org. 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.