add details to README

README.md

@@ -2,14 +2,9 @@
 
 This is a repository for materials to complete the NEON Ecological Forecasting Challenge tutorial. This tutorial repository is a dynamic repository and may change in future iterations.
 
-The tutorial is designed as a 90-minute, standalone session that includes an
-introductory presentation, a guided demonstration of forecast code, and open
-time for discussion. If a longer time period is available, the tutorial has
-additional activities and content that includes more advanced topics (Figure
-1). In addition, the tutorial can be completed by individuals at their own
-pace, without a dedicated instructor.
+The tutorial is designed as a 90-minute, standalone session that includes an introductory presentation, a guided demonstration of forecast code, and open time for discussion. If a longer time period is available, this repository has additional activities and content that includes more advanced topics. These materials can also be completed as a self-paced tutorial.
 
-## Pre-tutorial preparation
+## 1. Pre-workshop intructions
 
 ### Setting up your R environment
 
@@ -52,23 +47,33 @@ More information on forking and cloning in R can be found at [happygitwithr](htt
 
 For the workshop you can follow along via the rmarkdown document (`Submit_forecast/NEON_forecast_challenge_workshop_aquatics.Rmd`) or the md (`Submit_forecast/NEON_forecast_challenge_workshop_aquatics.md`), both of which can be downloaded here or you can fork the whole repository.
 
-## Introductory presentation
+## 2. Introductory presentation
 
-## Coding walk-through
+An introductory presentation that covers key forecasting concepts and a broad introduction the the Challenge and NEON data is available as both a PowerPoint or PDF. This presentation can be tailored to the audience based on expected familiarity with forecasting concepts and the data being forecasted.
+
+## 3. Coding walk-through
 
 The hands-on materials are split into three sections:
 
 1.  `Submit_forecast` - want to get started with making and submitting forecasts to the Challenge - start here!
 2.  `Automate_forecasts` - you've made a model and submitted a forecast successfully? Automate your workflow to submit a new forecast every day
 3.  `Analyse_scores` - interested in knowing how different forecasts are performing within the Challenge? This is a brief introduction in how to access the scored forecasts and do some simple analyses.
 
-## Open time
+For a 90-minute workshop, the hands-on R markdown walk through uses the materials in the `Submit_forecast` directory (30-40 minutes). The Rmarkdown includes descriptive text to reinforce some of the ideas introduced in the presentation and guides participants through the stages of forecast development from importing 'target' data (observations), plotting and investigating data, developing a model, generating a forecast, adjusting the format to Challenge standards, and submitting their forecast to the Challenge. 
+
+Materials in the other directories are recommended for later completion and cover more advanced topics (see Tutorial extension). 
+
+## 4. Open time
+
+For a standard 90-minute workshop, time at the end of the session can be used to debug user-specific code issues (package installation etc.), allow participants to modify the forecast model code available in the template (forecast_code_template.R), explore alternative forecast methods, or form forecasting teams to submit additional forecasts to the Challenge beyond the workshop session. Some potential topics and additional activities are detailed at the end of the Rmarkdown, including code for alternative forecasting methods or possible modifications to the example forecast. 
+
+## 5. Tutorial extension
 
-## Tutorial extension
+To extend the tutorial beyond 90 minutes, we have provided materials that walk participants through how forecast submission could be automated (`Automate_Forecast`). Automation is a crucial step for iterative, near-term ecological forecasting, and is highly encouraged when participating in the Challenge after completing the tutorial. Finally, materials are available that introduce participants to how a forecast is evaluated and how the scores (evaluated forecast performance) can be analysed (`Analyse_Scores`). These materials could also be used in a self-paced manner after a workshop.
 
 ### Optional: Use Docker
 
-Another alternative to running the materials locally is to use a Docker container that has all the packages pre-installed.
+Analternative to running the materials locally, is to use a Docker container that has all the packages pre-installed.
 
 #### Installing Docker
 
@@ -93,4 +98,4 @@ This can take a few minutes to download and install. It will be quicker the next
 
 You can close this localhost window (and then come back to it) but if you close the container from Docker (turn off your computer etc.) any changes will be lost unless you push them to Github or exported to your local environment.
 
-Then follow the instructions for Getting the Code above (`2. Get the Code`).
+Then follow the instructions for Getting the Code above (`2. Get the Code`).