Make Your Research Reproducible
RStudio® and RStudio Connect make data analysis easier and provides powerful tools for sharing a spectrum of data products, static or dynamic, developed in R and Python: Dashboards, applications, APIs, reports, and so much more.
RStudio® offers an open-source, development environment for users to perform data analysis on their local workstation. The RStudio environment links to RStudio Connect to enable users to share their research findings to others.
RStudio Connect is a standalone publishing platform for the work your teams create in R or Python. Share Shiny applications, R Markdown reports, dashboards, plots, models, Jupyter Notebooks, and more. Rstudio Connect can even be automated to update your content whenever you submit a commit to Git.
Who has access to RStudio Connect?
- Access to RStudio Connect is restricted to faculty, staff and students of the University of Arizona.
- Applicants must have a faculty member or research staff member as a sponsor. (Faculty and research staff may sponsor themselves.)
- There are a limited number of RStudio Connect user seats available to campus. Seat assignments will be reviewed each semester and sponsoring faculty may be asked about renewals. It is recommended that research groups designate one, at most two, users to be responsible for publishing materials on behalf of the lab group.
Are there any limitations on use?
- Publishing via RStudio Connect is for research purposes. It is not to be utilized for course assignments. Faculty and students wanting to publish in relation to course activities should first use the public Shiny App services (see https://www.shinyapps.io/).
- The expectation is that all published apps should be set to be publicly viewable. Requests should be made if viewing of the published materials needs to be limited or restricted.
- Rstudio Connect is provided for distribution of lightweight apps. Users needing greater compute power or large amounts of local storage should consider using the UA High Performance Computing System or CyVerse.
RStudio Connect is offered to the UArizona Campus through funding from UA Strategic Initiative: UAHS 5.3 - Health Analytics Powerhouse.
Resources and Support
There are several options for on-campus, in-person support.
- Jeff Oliver in the University Libraries offers R Programming Help and Workshops.
- The Data Science Team in the College of Agriculture, Life & Environmental Sciences (CALES) offers office hours, workshops and research support.
- Reach out to one of the campus Data Science Ambassadors.
- Connect and ask questions to other R-users on the UA Data Science Slack Workspace(link is external) (see the #r and #r-help channels)
There are many useful guides and tutorials online. Here are a few that are particularly useful.
- A tutorial on Building Interactive Web Apps with Shiny,(link is external) by Jeff Oliver in the University Libraries
- A series of articles from Shiny by RStudio stepping you through publishing your first app using Shiny(link is external)
- A guide on How to Embed a Shiny App in a Website(link is external)
- A post on how to Dockerize Shiny Applications (link is external)from R-bloggers.com
- RStudio offers a variety of resources to help you on your data science journey:
- The Carpentries offer a variety of workshops and curricula(link is external) for Data Carpentry and Software Carpentry using R, Python and RStudio
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