big 3 changes from o. fox

content/intro.md

@@ -3,22 +3,26 @@
 <span style="font-variant:small-caps;">the rsp is still in active development! your feedback will help us prioritize improvements.</span>
 
 
-The Roman Science Platform (RSP) enables you to access, simulate, visualize, and analyze data from the Nancy Grace Roman Space Telescope without installing or downloading anything on your own computer. You can open a new Python Jupyter notebook via the top menu (<span style="font-variant:small-caps;">file › new › notebook</span>)
+The Roman Science Platform (RSP) enables you to access, simulate, visualize, and analyze data from the Nancy Grace Roman Space Telescope without installing or downloading anything on your own computer. The RSP is accessed through JupyterLab, allowing you to run Jupyter Notebooks and scripts to perform a scientific analysis.
+You can open a new Python Jupyter notebook via the top menu (<span style="font-variant:small-caps;">file › new › notebook</span>)
 or use the links below to learn more.
 
-<img src="../images/icons/jupyter.svg" style="vertical-align: middle; width:1.5em; margin-right:0.25em;"/> [How do I use the Jupyter Interface?](../markdown/jupyter.md)
+<img src="../images/icons/question_mark.svg" style="vertical-align: middle; width:1.5em; margin-right:0.25em;"/> [RSP Overview](../markdown/what-is-rsp.md)
 
-<img src="../images/icons/question_mark.svg" style="vertical-align: middle; width:1.5em; margin-right:0.25em;"/> [What is the RSP?](../markdown/what-is-rsp.md)
 
-<img src="../images/icons/learning.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Roman Science Workflows](../markdown/workflows.md) and [Notebook Tutorials](../markdown/tutorials.md)
+<img src="../images/icons/jupyter.svg" style="vertical-align: middle; width:1.5em; margin-right:0.25em;"/> [Getting Started with Jupyter](../markdown/jupyter.md)
 
-<img src="../images/icons/database.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [What data are available?](../markdown/simulated-data.md)
+<img src="../images/icons/learning.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Roman Science Workflows](../markdown/workflows.md)
 
-<img src="../images/icons/download.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [How do I install extra software?](../markdown/software.md)
+<img src="../images/icons/book-stack.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [All Notebook Tutorials](../markdown/tutorials.md)
 
-<img src="../images/icons/cloud_download.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Best practices for cloud data](../content/notebooks/data_discovery_and_access/data_discovery_and_access.ipynb)
+<img src="../images/icons/database.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Available Data](../markdown/simulated-data.md)
 
-<img src="../images/icons/team.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [How do I work on a team?](../markdown/teams.md)
+<img src="../images/icons/cloud_download.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Data Discovery and Access](../content/notebooks/data_discovery_and_access/data_discovery_and_access.ipynb)
+
+<img src="../images/icons/team.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Working on a Team](../markdown/teams.md)
+
+<img src="../images/icons/download.svg" style="vertical-align: bottom; width:1.5em; margin-right:0.25em;"/> [Installing extra software](../markdown/software.md)
 
 <img src="../images/icons/book.svg" style="vertical-align: middle; width:1.5em; margin-right:0.25em;"/> [Roman Space Telescope Documentation Home](https://roman-docs.stsci.edu/)
 

markdown/jupyter.md

@@ -1,5 +1,7 @@
 # Getting Started with Jupyter
 
+<span style="font-variant:small-caps;">note: the next version of the rsp will integrate the welcome tour; for now, this documentation remains</span>
+
 ## The Basics: How do I use the interface?
 The [try Jupyter](https://try.jupyter.org) site is a great place to begin; select the "JupyterLab" option, then start the "Welcome Tour". This interactive tour will give you a thorough walkthrough of the JupyterLab user interface. Once that tour is complete, you should open a new, blank notebook and begin the "Notebook Tour"; it explains how to write and run code in a notebook environment.
 

markdown/simulated-data.md

@@ -1,4 +1,4 @@
-# Simulated Data Products on the RSP
+# Available Data
 
 
 

markdown/software.md

@@ -1,4 +1,4 @@
-# Software on the Science Platform
+# Installing Extra Software
 As part of the science platform, STScI provides pre-installed software. You can also install your own software.
 
 <span style="font-variant:small-caps;">note:</span> Any commands given on this page must be entered into a terminal window. To open a new terminal window, select <span style="font-variant:small-caps;">file > new terminal</span> from the menu bar.

markdown/teams.md

@@ -1,4 +1,4 @@
-# RSP Team Structure and File Sharing
+# Working on a Team
 
 ## Accessing Team Resources
 When you log into the RSP, you will see options to log in: either using your personal account or via “team” accounts. Your team membership has been determined a priori for this validation stage. In the future, users will be able to manage their team membership through a web-based interface. The selection you make at this stage (personal or a specific team) determines who will be charged for the resources used during your session. In addition, you must select how many resources (CPUs and GBs of RAM) you want available during your session. 

markdown/tutorials.md

@@ -1,4 +1,4 @@
-# RSP Jupyter Notebooks Tutorials
+# All Notebook Tutorials
 ## What are Notebook Tutorials?
 In the Roman Science Platform (RSP) framework, a notebook tutorial refers to a Jupyter notebook demonstrating how to use a specific piece of code or tool. A set of predefined Jupyter notebook tutorials is available to demonstrate how to use tools and software for accessing, simulating, processing, visualizing, and analyzing Roman Wide Field Instrument (WFI) data within the science platform. Although the current content primarily focuses on WFI imaging mode, Jupyter notebook tutorials for spectroscopic products will be available by Winter 2024.
 

markdown/what-is-rsp.md

@@ -1,4 +1,4 @@
-# What is the Roman Science Platform?
+# RSP Overview
 
 The Roman Science Platform (RSP) is a set of services and tools to query, visualize, simulate, and analyze Roman data. The RSP operates on a web-based platform called [JupyterHub](https://docs.jupyter.org/en/latest/), allowing users to collaboratively work in [JupyterLab](https://jupyterlab.readthedocs.io/en/latest/) sessions. Here, they can create [Jupyter notebooks](https://docs.jupyter.org/en/latest/). As web-based platform, RSP is operating-system agnostic and can be run on any modern internet browser. A stable Python environment is provided and maintained, including many commonly-used packages, the [Roman STScI Data Pipelines](https://roman-docs.stsci.edu/data-handbook-home/roman-stsci-data-pipelines), and [Roman related simulation and analysis tools](https://roman-docs.stsci.edu/simulation-tools-handbook-home). Users can create their own environments (Python or otherwise) and [install custom software](software.md). 
 

markdown/workflows.md

@@ -1,4 +1,4 @@
-# Science Workflows
+# Roman Science Workflows
 In the Roman Science Platform (RSP) framework, a Notebook Tutorial refers to a Jupyter Notebook that demonstrates the use of a specific piece of code or tool. A Science Workflow is a combination of multiple Notebook Tutorials, along with accompanying documentation, that guides users through a specific science use case.
 
 Users can run the Jupyter Notebook Tutorials in any order or modify them to suit specific data or science goals. However, following the sequence outlined in the Science Workflows ensures a complete, end-to-end experience. Science Workflows are particularly beneficial for new users unfamiliar with Roman data, tools, and infrastructure, but they also offer a valuable starting point for experienced users aiming to apply them to their own datasets.