Update README.md

README.md

@@ -12,31 +12,61 @@ a `Dockerfile`.
 
 ## Join the challenge
 
-1. The simplest way to join the S2S AI Challenge is forking this renku project.
+### 1. The simplest way to join the S2S AI Challenge is forking this renku project.
 (Ensure you do not fork the gitlab repository, but the reku project).
 
 Fork this template renku project from https://renkulab.io/projects/aaron.spring/s2s-ai-challenge-template/settings.
 
-<img src="docs/fork_renku.png" width="300">
+<img src="docs/screenshots/fork_renku.png" width="300">
 
-2. Make the project private (so that other people do not steal your idea/code)
-3. Add the `scorer` user to your repo with Reporter permissions (this is the lowest view-only permission so that the scorer can check results)
-4. Add a gitlab variable with key `COMPETITION` and name `S2S-AI` (we can set whatever name we want here)
+### 2. Make the project private
+
+Now check out the gitlab repository by clicking on "View in gitlab".
+Under "Settings" - "General" - "Visibility" you can set your project private.
+
+<img src="docs/screenshots/gitlab_visibility.png" width="300">
+
+Now other people cannot steal your idea/code.
+
+### 3. Add the `scorer` user to your repo with Reporter permissions
+The scorer is not yet ready, but will follow this [verification notebook](https://renkulab.io/gitlab/aaron.spring/s2s-ai-competition-bootstrap/-/blob/master/notebooks/verification_RPSS.ipynb).
+
+### 4. Add a gitlab variable with key `COMPETITION` and name `S2S-AI`
+In the gitlab repository, under "Settings" -> "CI/CD" -> "Variables", add the
+`COMPETITION` key with value `S2S-AI`, so the `scorer` bot knows where to search
+for submissions.
+
+<img src="docs/screenshots/gitlab_variables.png" width="300">
+<img src="docs/screenshots/gitlab_add_variable.png" width="300">
 
 ## Contribute
 
+### 5. Start jupyter
 The simplest way to contribute is right from the Renku platform - 
 just click on the `Environments` tab in your renku project and start a new session.
 This will start an interactive environment right in your browser.
 
+<img src="docs/screenshots/renku_start_env.png" width="300">
+
+If the docker image fails initially, please re-build docker or touch the `enviroment.yml` file.
+
 To work with the project anywhere outside the Renku platform,
 click the `Settings` tab where you will find the
 git repo URLs - use `git` to clone the project on whichever machine you want.
 
-5. Train your Machine Learning model, using training data from https://github.com/ecmwf-lab/climetlab-s2s-ai-challenge or renku datasets
-6. Let the Machine Learning model perform subseasonal 2020 predictions as netcdf files
-7. Commit training notebook/pipeline and ML_prediction.nc with `git lfs`. 
-8. The `scorer` will fetch your predictions, score them with RPSS against recalibrated ECMWF real-time forecasts and add your score to the leaderboard at https://s2s-ai-challenge.github.io.
+### 6. Train your Machine Learning model
+using training data from https://github.com/ecmwf-lab/climetlab-s2s-ai-challenge or renku datasets
+
+### 7. Let the Machine Learning model perform subseasonal 2020 predictions
+and save them as `netcdf` files.
+
+### 8. `git commit` training pipeline and netcdf submission
+For later verification of the organizers, reproducibility and scoring of submissions,
+the training notebook/pipeline and submission file ML_prediction.nc with `git lfs`. 
+
+### 9. RPSS scoring by `scorer` bot
+The `scorer` will fetch your predictions, score them with RPSS against recalibrated ECMWF real-time forecasts.
+Your score will be added to the leaderboard at https://s2s-ai-challenge.github.io/#leaderboard
 
 ## Changing interactive environment dependencies