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.
paper
address geocoding; heterogeneous data integration; interactive data enrichment; semantic data enrichment;
English
IEEE International Conference on Big Data, BigData 2023 - 15 December 2023 through 18 December 2023
2023
Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
9798350324457
2024
3139
3143
none
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].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/467018
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