Solutions to "Just KNIME It!" Challenge 2 - Season 3

:sun_with_face: A new Wednesday starts, and here we come with a new Just KNIME It! challenge. :sun_with_face:

:earth_africa: CO2 emissions are rising and compromising our environment. :leaves: This week, let’s build a low-code report that tells us which regions of the globe and what sources are producing the most emissions.

Here is the challenge. Let’s use this thread to post our solutions to it, which should be uploaded to your public KNIME Hub spaces with tag JKISeason3-2.

:sos: Need help with tags? To add tag JKISeason3-2 to your workflow, go to the description panel in KNIME Analytics Platform, click the pencil to edit it, and you will see the option for adding tags right there. :slight_smile: Let us know if you have any problems!


Just to add a bit of clarity to the data set. The columns cement, coal, flaring, gas, oil and other represent the individual contributions to the CO2 column. I reordered the columns and added a SUM for visibility as data, just by how it’s organized, also has context.

Organized vs. Original


Thank you for your contribution. Additionally, please consider the following important points:

  1. The unit for CO₂ emissions is million metric tons.
  2. The column labeled “CO₂ per capita” actually represents CO₂ emissions per million people. This was determined by dividing the total CO₂ emissions by the values in the “CO₂ per capita” column and comparing the results with population data available online.

There is a similar dataset on Kaggle that can be referenced, with field (column) explanations.


Here’s my solution. In interest of full disclosure I used some parts of a workflow which was uploaded several years ago. I created a dynamic Single Selection widget so if the user changes the size of the input set it automatically is reflected in the widget list.


Well done rfeigel! Your dashboard look good!


1 Like

In this solution, I decided to split the report into two parts:

  1. View Report Year-wise :date::
    This section provides an overview of the performance of all countries based on the year selected by the user.

  2. View Report Country-wise :earth_africa::
    This section details the CO2 emissions based on the user’s country selection. Additionally, it allows the user to select and compare the performance of two countries.

My Solution Workflow link : Season 3 Challenge 2 – KNIME Community Hub

Happy KNIMEing :smiley:


Hi all,
Here is my solution.

You can see the world maps which show CO2 amount and CO2 per capita amount by coloring each country fields.

However I could not insert world map section to the report field. The section was generated by Generic Javascript view node using Google GeoChart… I could not find any solutions to generate a SVG image from the chart.

If anyone know the way to generate SVG image from google GeoChart and share some information about it, that would be much appreciated.


Hi @alinebessa ,

Today, I’ve uploaded solution for this challenge.


Do you have the possibility to continue with workflow and add PDF Report + send by email ?


Here is my solution. Thanks to the animated bar chart component! :smiling_face:


Rookie KNIMER on the road.
Would like to share with you all my solution for challenge 2. Open to discussion and suggestion for improvements!
JustKNIMEit challenge 2 solution-Kel


Hi all,
Here is my solution with PDF report.

Pie chart analysis on a world map shows that CO2 sources tend to vary by region.

Major sources of CO2 emissions in each region
Asia: coal
Middle East: gas
Western Europe: oil
Eastern Europe: coal
Africa: oil
Americas: oil and gas


Hi all,
Here is my solution:

I have created two types of dashboards.
The first one is designed to provide an overview of all the data.
You can drill down into specific information by using the year and region tags.

The second one is a summary of CO2 emission data for individual countries.
It includes a pie chart, CO2 emissions by fuel type, CO2 emissions per capita, and the rate of change over a year.


Hi all,
The emissions of each resource were normalized from 0 to 1 and displayed in a heat map. Thanks.


Helo KNIMErs,
This is my take to the ‘CO2 Emissions’ JKI S3 challenge.

I’ve concentrated the most on deploying analytical slicing for the different geographical hierarchies:

  • Region
  • Sub-region
  • Country

Enjoy coding :vulcan_salute:t3:


This is my solution.


Amasing solutions here
My one won’t be able to compete with these I guess
Unfortunately I still haven’t figured out what kind of report I should use so I used BIRT


Here’s my solution. I wanted to illustrate how the different countries rank in CO2 emissions by source, how the different sources have grown YoY over time and how each sources share of the total CO2 has developed over time.


I have identified a bug in the previous workflow; therefore a new version of the workflow has been uploaded (v1.1.0).
Now, the pie chart created by the Python View Node can be exported to PDF.