In seiner Funktionalität auf die Lehre in gestalterischen Studiengängen zugeschnitten... Schnittstelle für die moderne Lehre
In seiner Funktionalität auf die Lehre in gestalterischen Studiengängen zugeschnitten... Schnittstelle für die moderne Lehre
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.
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.
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.
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:
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.