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German Annual Air Emissions Visualized

The starting point of my project was a report by the German Environment Agency in 2021 on annual emissions data by sector since the 90's until 2019.

Dataset

My dataset consists of 30 tables with about 160 rows by 140 columns - really massive.

I started with a summary of annual emissions from the German Federal Environment Agency, but realized that I had massive gaps in the 90s. Then I found the original report published by the European Environment Agency with much more data - including high resolution categorization. Nevertheless, I only included the pollutants mentioned in the summary and excluded all heavy metals. This was because I already had a design and a working visualization.

Data Processing

I cleaned up the data using Jupyter notebooks and prepared a lot of different tables for the final web application - for example, aggregating categories so the browser doesn't have to do that.

Design and Development

First, I tried to force my visualization project to fit the topic of the course, but failed. My data was not really suitable for a network viz.

I tried several visual solutions, but they all lacked clarity and the ability to really explore the dataset.

I ended up iterating many, many times between development and going back to the drawing board to try new things.

Here are some examples of failed designs:

Screenshot 2022-04-04 at 16.39.23.pngScreenshot 2022-04-04 at 16.39.23.png
Screenshot 2022-04-04 at 16.39.02.pngScreenshot 2022-04-04 at 16.39.02.png
Screenshot 2022-04-04 at 16.39.15.pngScreenshot 2022-04-04 at 16.39.15.png
Screenshot 2022-04-04 at 16.39.37.pngScreenshot 2022-04-04 at 16.39.37.png
Screenshot 2022-04-04 at 16.39.30.pngScreenshot 2022-04-04 at 16.39.30.png
Screenshot 2022-04-04 at 16.40.07.pngScreenshot 2022-04-04 at 16.40.07.png
Screenshot 2022-04-04 at 16.40.17.pngScreenshot 2022-04-04 at 16.40.17.png
Screenshot 2022-04-04 at 16.40.24.pngScreenshot 2022-04-04 at 16.40.24.png
Screenshot 2022-04-04 at 16.40.31.pngScreenshot 2022-04-04 at 16.40.31.png
Screenshot 2022-04-04 at 16.40.45.pngScreenshot 2022-04-04 at 16.40.45.png
Screenshot 2022-04-04 at 16.40.56.pngScreenshot 2022-04-04 at 16.40.56.png
Screenshot 2022-04-04 at 16.41.13.pngScreenshot 2022-04-04 at 16.41.13.png
Screenshot 2022-04-04 at 16.41.26.pngScreenshot 2022-04-04 at 16.41.26.png
Screenshot 2022-04-04 at 16.41.41.pngScreenshot 2022-04-04 at 16.41.41.png
Screenshot 2022-04-04 at 16.42.24.pngScreenshot 2022-04-04 at 16.42.24.png
Screenshot 2022-04-04 at 16.45.13.pngScreenshot 2022-04-04 at 16.45.13.png

Result

Screenshot 2022-04-04 at 17.17.56.pngScreenshot 2022-04-04 at 17.17.56.png
Screenshot 2022-04-04 at 17.18.07.pngScreenshot 2022-04-04 at 17.18.07.png
Screenshot 2022-04-04 at 17.18.35.pngScreenshot 2022-04-04 at 17.18.35.png
Screenshot 2022-04-04 at 17.17.45.pngScreenshot 2022-04-04 at 17.17.45.png
Screenshot 2022-04-04 at 17.18.16.pngScreenshot 2022-04-04 at 17.18.16.png

In the end I am quite satisfied with the result. As I said, it does not really fit the topic of the course, but for the real first steps on data viz ground I am quite satisfied.

This semester has awakened my interest in data visualization and I am curious to see what will come in the future.

github source

Data Visualization

Ein Projekt von

Fachgruppe

Interfacedesign

Art des Projekts

Studienarbeit im zweiten Studienabschnitt

Betreuung

foto: Mark-Jan Bludau

Zugehöriger Workspace

Advances in Data Visualization: Networks & Hierarchies

Entstehungszeitraum

Wintersemester 2021 / 2022

Keywords