modify text for this event

Author: aaarendt

book/preliminary/index.md

@@ -1,42 +1,31 @@
 # What to Expect 
 
 Our hackweeks focus on applied, hands-on learning, with participants engaging in
-extended periods of small-group work. Our tutorials are designed to offer a broad
-snapshot of data science tools to support your applied investigations. Due to the
-relatively short duration of our events, we are not able to provide comprehensive,
-in-depth training in fundamental tools. Rather, our goal is to inform you about
-the types of tools we think are best suited to working with your datasets,
-leaving details of implementation to be supported through peer-learning and
-office hours.
+extended periods of small-group work. Our tutorials are designed to offer a 
+broad snapshot of data science tools to support your applied investigations. 
+Due to the relatively short duration of our events, we are not able to provide 
+comprehensive, in-depth training in fundamental tools. Rather, our goal is to 
+inform you about the types of tools we think are best suited to working with 
+your datasets, leaving details of implementation to be supported through 
+peer-learning and office hours.
 
-## Typical Workflows and Tools
+In this hackweek we will focus on software development in support
+of the ICESat-2 mission. We'll center most of our work on streamlining
+data access patterns within the NASA earthaccess library. Our goal is to 
+make it easier for people to access ICESat-2 data and make informed decisions
+on which product, and which software solution, best supports their reserach 
+needs. We will also think about how to integrate data across multiple 
+(especially NISAR, but also GEDI, SnowEx, etc.).
 
-Here are a few specific scenarios of how hackweek participants typically engage
-with data science tools during an event:
-
-* Connecting to a [Jupyter Notebook](https://jupyter.org/) environment and using
-  the command line to pull lesson content for a morning of tutorial training.
-* Modifying a text file, committing it to Git and pushing changes to GitHub, for
-  others on your team to view and edit.
-* Opening CSV tabular data in Pandas and using filtering functions to remove
-  outliers.
-* Accessing a cloud-hosted remote sensing image using Rasterio and plotting it
-  on an interactive map.
-* Exploring multi-dimensional climate grids using xarray.
-
-These are examples of the types of activities we do at a hackweek in a
-collaborative setting. We invite you to reflect on your comfort level with tasks
-such as these so that you can arrive at the hackweek with a clarity on where to
-dedicate your energy. If wish to focus more energy on learning and implementing
-new tools, we will support you with helpers and office hours, and you may have a
-bit less time for applied group work. If you are already proficient in a lot of
-tools you may find you can dedicate more energy to applied project work, which
-we support through facilitated group activities.
+Due to the invitational nature of this particular hackweek, and the well-defined
+set of tasks, we will be focusing most activity on project work. There will 
+be a few short tutorials offered by colleagues from the UW Scientific Software
+Engineering Center.  
 
 ## Prerequisites
 
-All tutorials and project work will assume participants are familiar with Python-based
-computing in the geosciences as described on the 
-[Pythia Foundations](https://foundations.projectpythia.org/landing-page.html) website. 
- We can provide resources to participants wishing to brush up on their skills before
-an event, however we will not be teaching these core concepts during the hackweek.
+All tutorials and project work will assume participants are familiar with 
+Python-based computing in the geosciences as described on the 
+[Pythia Foundations](https://foundations.projectpythia.org/landing-page.html) 
+website. 
+