Scientists increasingly use interactive visualizations and simple analytical web applications (dashboards) to support publications and discussions, e.g. public debates, informed panel discussions or decision theatres. They allow analysts or decision makers to easily present, share and explore visualizations of model input or output data from anywhere (no installation requirements). As such applications increase the accessibility of model results or input data, they are a further step towards better transparency.
Examples of simple analytical web applications that already support publications and discussions:
model.energy, pypsa-eur-30-animation, possibility-for-electricity-autarky-map, wind power potential, renewables.ninja, hotmaps, riskmeter, idea-dash, energy charts, kombikraftwerk-2-animation
Proposed structure of the tutorial:
- What is plotly.express and dash?
- Demo of plotly.express and dash for energy data exploration
- Pros and cons of using dash for applications
- Create your own application in 30 minutes
It is recommended to have a look at the plotly with python tutorial by Bryn Pickering in advance.
Follow-up action could be a do-a-thon (1) for the discussion of use-case specific requirements for apps/dashboards for energy system analysis/exploration or (2) for conceptualizing a wrapper around dash for an even more productive development of simple analytical web applications for energy system analysis.
Would you like to be responsible for this Session?
Yes (Lukas Nacken, Uni Kassel)
Do you need any special infrastructure for this Session?
Projector, BYOD (bring your own device), eduroam/wifi
Do you have any recommendations who could be part of this Session?
Everyone who is interested in creating simple web apps for analyzing energy model data with a few lines of pure python code.