How did the COVID-19 regulations affect the hospitality industry in each of Germany's states?
Information visualization project for Lecture Information Visualization of the winter semester 2022-/23.
Available at: https://iv2223-projects.pages.gitlab.lrz.de/team-32/
| Felix Bastian | Simon Grätz | Janka Hartmann | Timy Phan | You Sun Song |
|---|---|---|---|---|
| Design & Code-Quality | Handyman | Project Management | Data Specialist | Ideation & Code |
Team member functions are fluid and everyone chips in with programming.
- Make sure Node.js version 18+ is installed (LTS recommended), includes npm.
- Install recommended project extensions for your code editor (see
.vscode/extensions.json). - Install project dependencies locally:
npm install - Start a local development server:
npm run dev
To the top left, the user can see a map of Germany (the state cities Hamburg, Bremen and Berlin were enlarged for better visibility and accessibility). The states are highlighted with different colors, based on which variable is selected in the top row and which point in time is selected in the timeline. Light coloring of a state indicates low values of the selected variable, while darker colors indicate higher values of the selected variable per state. Note that the color scale is constant across all points in time per variable, thus if e. g. Bavaria's coloring is more saturated at one chosen point in time, then it also has a higher value at that point.
COVID-19 regulation measures are indicated by red coloring of the otherwise gray bars above the states. The red color is filled bottom-up (akin to filling a vessel with liquid) and is derived from the Massnahmenindex Bundeslaender pro Monat. Note that COVID-19 regulations were first introduced in March 2020, thus there is no such red coloring in the months before that.
At the bottom, the user can see a timeline which shows the same variable as the map, but applied to all of Germany (map coloring is state-specific). Points in time can be selected at month-level granularity, like June 2020, by clicking on the timeline.
When a state is selected in the map, a second graph line appears in the line chart which represents the selected state for comparison.
- Map of Germany & its states: The variable which is selected at the top is represented as the coloring of each state. The split bars above the states indicate the severity of corona regulations at the selected time.
- Timeline representing information about Germany as a whole: The timeline shows the same variable as the map (the variable which is selected at the top). When a state is selected in the map, a second line is shown in the timeline which represents the selected state in addition to the line which represents Germany. A point in time can be selected via scrubber in the timeline or by using the playback feature.
- Switching between visualized datasets: revenue, number of employees, average 7-day-incidences per month
- Detail View representing additional information to the currently selected state: The Detailview is opened by clicking on a state. It contains Details on the selected states and charts representing one a yearly and one a national comparison.
- Play Button: On the left of the timeline is a play button. By clicking on it, an automatic timeline flow starts.
- Tutorial: A short tutorial in the beginning gives an Introduction to Covisualized and the information that can be retreived on the page.
- About Section: The About Section contains information about the five developers of Covisualized.
Used datasets (preprocessed for formatting and data reduction, filtered files can be found in src/assets/data)
- Hospitality revenue: Datasets 45213-0014 and 45213-0005 from https://www-genesis.destatis.de/.
- Number of employees in the hospitality industry: Datasets 45213-0002 and 45213-0012 from https://www-genesis.destatis.de/.
- Average 7 day incidence rate per month: Dataset RKI History from https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/6d78eb3b86ad4466a8e264aa2e32a2e4_0/about (Incidence rate was computed based on cumulative number of reported cases).
- Lockdown measures: The ZPID Lockdown Measures Dataset for Germany from https://www.psycharchives.org/en/item/8a0c3db3-d4bf-46dd-8ffc-557430d45ddd and the Massnahmenindex Bundeslaender pro Monat from https://www.corona-daten-deutschland.de/dataset/massnahmenindex_bundeslaender_pro_monat.
Notes:
- Revenue and number of employees values are relative and use revenue or number of employees from 2015 as a reference value. Revenue or number of employees from 2015 is represented as 100%. Thus, if e.g. revenue has increased by 10% since 2015, it is shown as 110%.
- Average 7 day incidence rate per month: The incidence rate was not given but calculated based on the number of reported cases in RKI History.