The demand for energy is increasing worldwide. In Europe, creating sustainable energy resources is an important point on the political agenda. However, there are changes in the exact needs of renewable energy through space and time, with changes in for example demography, migration and technological developments. A Decision Support System (DSS) is required for policy makers to get an overview of different future scenarios in terms of energy demands. Such a DSS tool should be based upon a database, containing the relevant data, and a decision analysis model that uses these data.

Your task will be:
- Find and explore data that could potentially be related to spatial and temporal variability in energy consumption (e.g. population density, age, education level, energy price, etc.). Depending on data availability and your interests, this can either be at a local level (e.g. per municipality/province) or at a regional level (e.g. per country in Europe).
- Analyze the data to explore relations and dependencies. Find the most important indicators for energy consumption which could vary in space and/or time. Build a model to predict energy demand based on these indicators.
- Design and implement a DSS to visualize the results in space (maps) and time (graphs) to allow for efficient decision making.