Data enrichment facilitates the creation of rich, expressive, and high-quality datasets, enabling valuable analytics and enhanced decision-making. The accurate geolocation of residential addresses and travel routes is crucial for determining the most appropriate locations of critical social infrastructure, such as educational and medical centres. This paper introduces an interactive semantic enrichment approach that enhances urban data by integrating high-quality geospatial information. The approach is supported by a modular and extensible data enrichment framework, which leverages existing geolocation services, enabling seamless data integration. Human-in-the-loop revision is employed to enhance the quality of geocoding results. A real-world pilot study conducted in Sofia, Bulgaria, was used to validate this approach, demonstrating its promising potential in addressing pressing issues in parametric urban planning.
Krasteva, I., Petrova-Antonova, D., De Paoli, F., Hristov, E., Borukova, M., Ciavotta, M., et al. (2024). Geospatial Enrichment of Urban Data for Advanced City Planning: a Pilot Study. In Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023 (pp.3139-3143). Institute of Electrical and Electronics Engineers Inc. [10.1109/BigData59044.2023.10386822].
Geospatial Enrichment of Urban Data for Advanced City Planning: a Pilot Study
De Paoli F.
;Ciavotta M.;Avogadro R.
2024
Abstract
Data enrichment facilitates the creation of rich, expressive, and high-quality datasets, enabling valuable analytics and enhanced decision-making. The accurate geolocation of residential addresses and travel routes is crucial for determining the most appropriate locations of critical social infrastructure, such as educational and medical centres. This paper introduces an interactive semantic enrichment approach that enhances urban data by integrating high-quality geospatial information. The approach is supported by a modular and extensible data enrichment framework, which leverages existing geolocation services, enabling seamless data integration. Human-in-the-loop revision is employed to enhance the quality of geocoding results. A real-world pilot study conducted in Sofia, Bulgaria, was used to validate this approach, demonstrating its promising potential in addressing pressing issues in parametric urban planning.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.