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SUBMISSION INSTRUCTIONSETL process for combining 50 (open) data sets to get deep insights in the public owned real estate of the city Rotterdam (625.000 inhabitants, > 1.300 building) Our 'higher goal' is to make sure public money is spent in the most efficient way. With our Smart City tool we create insights in the performance of the public real estate. Based on these insights the (local) government can improve it's performance (less real estate facilities to reach the same goals and better financial performance of facilities).
With our Smart City solution, we combine all kinds of data sets (demographic, social, technical) to get a broader and deeper insight in the performance of public owned real estate. We combine data from the buildings and the inhabitants of the city and benchmark the performance with other cities. For example: we measure the number, variety and accessibility of sport facilities in the city and combine these data with the health of the inhabitants. Or we give insights in the effect of the number and variety of primary schools in a neighborhood compared to the number of unemployment rates.
We combine a lot of different types of input files (csv, xlsx, shp, txt, pdf and mysql), combine data and make analyses (also analyses, for example a distance-analyses for each postal zone to the nearest schools and sport facilities). We write output to our MySQL database, write export files for visualization in Tableau and spatial output files (shp).