Open Source Web Applications

These web applications are hosted and managed by the staff in Teaching & Learning with Technology to support courses and instruction. They are freely available for all students, faculty and staff. No registration is required. 

Server maintenance is scheduled for Thursday, December 20th from 5-7am. During that time access to RStudio Server, JupyterHub, and RStudio Connect may be unavailable or intermittent. The software applications and associated packages will be updated during that time. For questions or concerns, please contact – CHG0056713


Penn State students, faculty, and staff can access these web applications from any modern web browser by using a Penn State Access Account username and password. A VPN connection is required when connecting from a non-university (off-campus) network. For more information on using the Penn State VPN service (ISPtoPSU), please visit this knowledgebase article.

Your personal PASS storage space is mounted as the working directory, therefore you can utilize tools like WebFiles or the LAT computer lab systems to transfer data files to PASS and they will be accessible within the web applications.


Jupyter iconJupyter is an interactive coding environment which offers a variety of programming languages, such as Python and R, to perform live data manipulation and analysis, and combines it with rich inline markdown text. Documents created in Jupyter are saved in the Jupyter notebook format, which can be easily shared or exported and published in a variety of formats, such as html, PDF and Microsoft Word.

Login to Jupyter

R iconRStudio Server is a web version of the popular RStudio desktop application, which is an integrated development environment for the open-source R statistical programming language. It provides powerful coding and debugging tools as well as rich data visualization and publishing tools.

Login to RStudio


RStudio Connect icon

RStudio Connect is a publishing platform for R. It allows easy push-button publishing of R documents and Shiny applications. It provides the ability to self-manage your content, or to add project collaborators, and to control access to who can access your published content. Advanced features include scheduled updates, report generation, email updates, REST APIs, and ODBC data connectors. For more information, view the RStudio Connect User Guide.

Login to RStudio Connect


For help, questions, or to request the installation of additional Python modules, Jupyter environments, R versions, or R packages please submit a support request.


We welcome any feedback and opportunities to discuss collaborations for teaching or other academic projects – please email us at