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53 changes: 53 additions & 0 deletions topics/climate/tutorials/ocean-variables/tutorial.bib
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# This is the bibliography file for your tutorial.
#
# To add bibliography (bibtex) entries here, follow these steps:
# 1) Find the DOI for the article you want to cite
# 2) Go to https://doi2bib.org and fill in the DOI
# 3) Copy the resulting bibtex entry into this file
#
# To cite the example below, in your tutorial.md file
# use {% cite Batut2018 %}
#
# If you want to cite an online resourse (website etc)
# you can use the 'online' format (see below)
#
# You can remove the examples below
@article{Batut2018,
doi = {10.1016/j.cels.2018.05.012},
url = {https://doi.org/10.1016/j.cels.2018.05.012},
year = {2018},
month = jun,
publisher = {Elsevier {BV}},
volume = {6},
number = {6},
pages = {752--758.e1},
author = {B{\'{e}}r{\'{e}}nice Batut and Saskia Hiltemann and Andrea Bagnacani and Dannon Baker and Vivek Bhardwaj and
Clemens Blank and Anthony Bretaudeau and Loraine Brillet-Gu{\'{e}}guen and Martin {\v{C}}ech and John Chilton
and Dave Clements and Olivia Doppelt-Azeroual and Anika Erxleben and Mallory Ann Freeberg and Simon Gladman and
Youri Hoogstrate and Hans-Rudolf Hotz and Torsten Houwaart and Pratik Jagtap and Delphine Larivi{\`{e}}re and
Gildas Le Corguill{\'{e}} and Thomas Manke and Fabien Mareuil and Fidel Ram{\'{i}}rez and Devon Ryan and
Florian Christoph Sigloch and Nicola Soranzo and Joachim Wolff and Pavankumar Videm and Markus Wolfien and
Aisanjiang Wubuli and Dilmurat Yusuf and James Taylor and Rolf Backofen and Anton Nekrutenko and Bj\"{o}rn Gr\"{u}ning},
title = {Community-Driven Data Analysis Training for Biology},
journal = {Cell Systems}
}

@online{gtn-website,
author = {GTN community},
title = {GTN Training Materials: Collection of tutorials developed and maintained by the worldwide Galaxy community},
url = {https://training.galaxyproject.org},
urldate = {2021-03-24}
}

@misc{hcmrdata,
doi = {10.13120},
url = {https://doi.org/10.13120/a51003ee-d2ab-4b6c-a4ca-c95d1d872018},
author = {{Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)}},
keywords = {oceans, environment, global ocean observing system, ocean circulation, in-situ, ocean pressure, sea water salinity, sea water temperature, multi-year, weather climate and seasonal observation, global-ocean},
title = {Mediterranean Sea - Eutrophication and Acidity aggregated datasets 1911/2022 v2022},
publisher = {EMODnet Chemistry},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}
273 changes: 273 additions & 0 deletions topics/climate/tutorials/ocean-variables/tutorial.md
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---
layout: tutorial_hands_on

title: Ocean's variables study
questions:
- How to process extract ocean's variables?
- How to use ODV collections?
- How to create climatological estimates?
objectives:
- Deals with ODV collection with data orginating from Emodnet chemistry
- Visualise ocean variables in order to study climate changes
time_estimation: 1H
key_points:
- Manage ODV collection's data.
- Learn to extract data and visualize them on ODV
- Learn to chain ODV and DIVAnd
tags:
- earth-system
- ocean
- geographical information system
- ODV
- netcdf data
- maps
- marine data
- climate
contributions:
authorship:
- Marie59
funding:
- fairease
- eurosciencegateway
---


# Introduction


Through this tutorial, you will learn in the first part how to import, visualise, and extract data from an ODV collection by using the ODV Galaxy interactive tool. In the second part, you will learn how to use DIVAnd using the inputs the outputs from ODV.

Ocean Data View (ODV) is a software package for the interactive exploration, analysis and visualization of oceanographic and other geo-referenced profile, time-series, trajectory, or sequence data. To know more about ODV go check the [official page](https://odv.awi.de/)

DIVAnd (Data-Interpolating Variational Analysis in n dimensions) performs an n-dimensional variational analysis/gridding of arbitrarily located observations. Observations will be interpolated/analyzed on a curvilinear grid in 1, 2, 3 or more dimensions. See the [official page](https://gher-uliege.github.io/DIVAnd-presentation/#1)

> <agenda-title></agenda-title>
>
> In this tutorial, we will cover:
>
> 1. TOC
> {:toc}
>
{: .agenda}

# Managing ODV Galaxy interactive tool
ODV is now integrated in Galaxy as an interactive tool. This kind of tool works differently than classical tools as it allows the user to interact in an interactive way with your data.
This kind of tool is used to give access to Jupyter notebooks, RStudio or R Shiny apps for example.

To use ODV, you need to use the {% tool [dedicated form](interactive_tool_odv) %}, you can specify input datasets from your history you want to use in ODV, then press the **execute** button to launch an ODV instance. When the graphical user interface of ODV is ready to be used, a URL will be displayed at the top of the Galaxy center panel. If you don't see it, you can see and access it through the "Active InteractiveTools" space of the "User" menu or you can click on {% icon galaxy-eye %} on the tool in the history.

Once you finish your work on ODV, if you want to retrieve data and/or the entire project, you need to save files in ODV/galaxy/outputs, then quit ODV properly through the "Project" Menu tab.

> <details-title>Short introduction on how Galaxy works</details-title>
>
> You can come back to where you left off the tutorial anytime by clicking {% icon level %}.
>
> > <hands-on-title>Log in to Galaxy</hands-on-title>
> > 1. Open your favorite browser (Chrome, Safari or Firefox as your browser, not Internet Explorer!)
> > 2. Browse to your [Galaxy instance](https://earth-system.usegalaxy.eu/)
> > 3. On the top panel go to **Login or Register**
> >
> >
> {: .hands_on}
>
> The Galaxy homepage is divided into three panels:
> * Tools on the left
> * Viewing panel in the middle
> * History of analysis and files on the right
>
> ![Screenshot of the Galaxy interface, the tools panel is on the left, the main panel is in the center, and the history is on the right.]({% link shared/images/galaxy_interface.png %} "Galaxy interface explanation")
>
> The first time you use Galaxy, there will be no files in your history panel.
{: .details}


> <hands-on-title>Deploy your own ODV instance</hands-on-title>
>
> 1. Create a new history for this tutorial and give it a name (for example “Ocean's variables”) for you to find it again later if needed.
>
> {% snippet faqs/galaxy/histories_create_new.md %}
>
> 2. Import a ODV collection data locally as a zip folder.
>
> {% snippet faqs/galaxy/datasets_upload.md %}
>
>
> 3. {% tool [Ocean Data View](interactive_tool_odv) %} with the following parameters:
> - *"Select if you are using an ODV collection in a zip folder or if you have your own raw data"*: `The data you are using are an ODV collection in a zip folder`
> - *"ODV collection in a zip folder."*: `Eutrophication_Med_profiles_2022_unrestricted_SNAPSHOT_2023-10-24T16-39-44.zip`
>
> ![Screenshot of what parameters to input in ODV before running the tool](../../images/ocean_var/launching_odv.png)
>
> 4. Click on **Run Tool**
>
> {% snippet faqs/galaxy/interactive_tools_open.md tool="ODV" %}
>
{: .hands_on}


> <details-title> Some complementary information about your data </details-title>
> The data here are Mediterranean Sea - Eutrophication and Acidity aggregated datasets
> EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity, and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity and covers the Mediterranean Sea. Data were aggregated and quality controlled by the 'Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)' in Greece.
>
> ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
>
> Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality-controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
>
> When not present in the original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L. {% cite hcmrdata %}
>
>
{: .details}

# Ocean Data View
## Visualise your Data

> <tip-title>Copy pasting between computer and ODV</tip-title>
> You can expand the ODV left panel (where there are 3 dots, vertically) to access the "clipboard" menu and paste the content you want to paste on an ODV form. From there you can copy-paste everything from one side to the other. Then, click outside of this panel to collapse it.
>
> ![Image showing in transparent on the left of the ODV interface the clipboard](../../images/coastal_water_dyn/clipboard.png)
{: .tip}

> <tip-title>ODV - Disconnected</tip-title>
> If at one point your ODV interface becomes grey with a red panel on the top "X ODV - Disconnected", do NOT panic ;) you just need to reload your tab (circular arrow top left)
{: .tip}

> <hands-on-title>Loading data</hands-on-title>
>
> 1. Click on close of the pop-up screen for the check for Updates
> 2. Go the top left and click on **File**, then on **Open...**
> 3. On the pop-up screen on the left panel select **ODV**, then the folder **galaxy**, then **data**.
> You should see a folder open it (double clicking)
> 4. Select the file with a .odv extension
> ![Screenshot of what your pop-up screen should be like when selecting the right data](../../images/ocean_var/select_data.png)
> 5. Click on **Open** in the bottom right
>
> There your data should be opening an you can now visualise them!
{: .hands_on}
![Visualistation on an ODV map of the ODV collection](../../images/ocean_var/visualise_data.png)

> <question-title></question-title>
>
> 1. What are the longitude and latitude of the red dot?
>
> > <solution-title></solution-title>
> >
> > 1. On the to right window you can read Longitude 34°E and Latitude 32.332°N.
> >
> {: .solution}
>
{: .question}

## Subset Data

> <hands-on-title>Create a subset</hands-on-title>
> 1. On the left smaller map right click and select **Zoom**
> 2. Then move your cursor on the map you should see a red rectangle moving along
> 3. Reduce the rectangular to have the selection you want on the map. It can be something similar to the following image (no need to be exactly the same)
> ![Selection on the map of the part of the data that you want to analyse](../../images/ocean_var/select_subset.png)
> 4. Once you're happy with your selection click on **Enter** on your keyboard.
> ![Result of the subsetting and how the maps should look now](../../images/ocean_var/subset.png)
>
> Here you have created a a subset of your data.
{: .hands_on}

> <tip-title>Change your visualisation properties</tip-title>
> 1. Go to the central map
> 2. Click right and select **Properties...**
> 3. For example, make your data dots bigger in "Display Style" increase the number below "Symbol Size" to 50, and click **OK**
> ![Image on how to change the size of your dots](../../images/ocean_var/size_dots.png)
>
> You can now see bigger dots representing your data.
> ![Image of your maps after the increase of the dots' size](../../images/ocean_var/big_dots.png)
>
> If you want to save it now that you already saved it once in the right folder outputs you just have to click lef on te save icon top left when it's red.
{: .tip}

## Save Data
{% include _includes/cyoa-choices.html option1="xview" option2="png" default="png"
text="Here you can choose if you want to save your view as an ODV view in xview format (you will not able to directly visualise it on Galaxy) or if you want to save it in png which you can visualise on Galaxy." %}
<div class="xview" markdown="1">
> <hands-on-title>Save your subset view</hands-on-title>
> 1. On the top left of your screen, you can see a red save button. Right-click on it.
> 2. In the pop-up screen go to the folder **ODV**, **galaxy**, **outputs**.
> 3. In **File name** rename your view (for example subset_Eutrophication_Med_profiles_2022), and **Save**.
{: .hands_on}
</div>
<div class="png" markdown="1">
> <hands-on-title>Save your subset map</hands-on-title>
> 1. Click right on the map and select **Save Plot As...**
> 2. In the pop-up screen go to the folder **ODV**, **galaxy**, **outputs**.
> 3. In **File name** rename your view (for example subset_Eutrophication_Med_profiles_2022_1)
> 4. In **Files of type** select `PNG (*.png *.PNG)` and **Save** then **OK** and **OK**.
{: .hands_on}
</div>


> <hands-on-title>Extract your variables in netcdf data</hands-on-title>
> Now we want to extract and save the right parameters of your data in netcdf format.
> 1. Go to the the left and click on **Export**, **Data** and **NetCDF File...**
> 2. In the pop-up screen go to the folder **ODV**, **galaxy**, **outputs**.
> 3. Click **Save**
> 4. A new pop-up window opens "Select Extended Metadata Variables for Export" Let the 56 items selected and click **OK**
> 5. "Select Data Variables for Export" `here you need to select 1: Depth[m]`, ̀`4: Water body dissolved oxygen concentration [umol/l]`, `6: Water body phosphate [umol/l]` and click **OK**
> ![Screenshot of the variables one needs to select](../../images/ocean_var/select_var.png)
> 6. "NetCDF File Properties" change the **Longitude range** to `[-180 ... 180] degrees_E`, then select `Export metadata quality flags` and `Export data quality flags` and **OK**.
> 7. And **OK** again
>
> You now know how to export and save the right variables on ODV to netCDF data.
{: .hands_on}

Now, if you have finished with your analysis you can exit ODV. To do so you need to do it properly.

> <hands-on-title>Exit ODV and go back on Galaxy</hands-on-title>
> 1. On the top left click on **File** select **Exit**
> 2. If you want to save the other window also click on **Yes**. Here we don't need it so click **No**.
>
> You can now go back to your Galaxy instance.
> Now, after waiting for everything to turn green in your history, you can see 3 new outputs
> ![Screenshot of the 3 new outputs present in your galaxy History](../../images/ocean_var/history.png)
>
> In the history panel click on the {% icon galaxy-eye %} (eye) icon of your output.
>
> You can now visualize the outputs in Galaxy middle panel.
>
> ![Screenshot of the text output showing the variables selected](../../images/ocean_var/text.png)
> ![Image in the middle pannel of the map](../../images/ocean_var/galaxy_output.png)
{: .hands_on}

# DIVAnd : Data-Interpolating Variational Analysis in n dimensions

## Change Datatype
> <hands-on-title>Change the datatype from ODV outputs</hands-on-title>
> Go to your output 'data_from_Eutrophication_Med_profiles_2022_unrestricted'
>
> In the Datatypes section select **netcdf**
>
> {% snippet faqs/galaxy/datasets_change_datatype.md %}
>
{: .hands_on}

## Launch DIVAnd
Use ODV outputs (which you just changed the datatype) as DIVAnd input.
> <hands-on-title>Run DIVANnd</hands-on-title>
>
> 1. Use {% tool [DIVAnd](interactive_tool_divand) %} with the following parameters:
> - *"Do you already have a notebook"*: `Start with a fresh notebook`
> - *"Include data into the environment"*: `data_from_Eutrophication_Med_profiles_2022_unrestricted`
> 2. **Run tool**
> 3. {% snippet faqs/galaxy/interactive_tools_open.md tool="DIVAnd" %}
{: .hands_on}

Now that you are in your jupyterlab with the right environment to use DIVAnd and a set of notebooks (in the folder **notebooks**) to guide you, you can start the rest of your analysis.
You can find your data from ODV in the **data** folder of the jupyterlab.

Once you are done you have to save all your wanted data and visualisation in the **outputs** folder and then go to the top left in the **file** section and click on **Exit**.

After a couple of minutes, your outputs should appear in your Galaxy history.


# Conclusion

Great you now know how to extract ocean variables from an ODV collection and use these extracted data in DIVAnd.

# Extra information
Coming up soon follow-up tutorials on Coastal Water Dynamics workflow (and other Earth-System related trainings). Keep an {% icon galaxy-eye %} open if you are interested!

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