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English Information

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Authors
# Name
1 Lyncoln de Oliveira(oliveiral@cos.ufrj.br)
2 Gustavo Moreira(gmorei3@uic.edu)
3 Fábio Miranda(fabiom@uic.edu)
4 Marcos Lage(mlage@ic.uff.br)
5 Daniel de Oliveira(danielcmo@ic.uff.br)

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Reference
# Reference
1 Ang, L.-M. and Seng, K. P. (2016). Big sensor data applications in urban environments. Big Data Research, 4:1–12.
2 Bavoil, L., Callahan, S. P., Crossno, P. J., Freire, J., Scheidegger, C. E., Silva, C. T., and Vo, H. T. (2005). Vistrails: enabling interactive multiple-view visualizations. In IEEE Vis 2005, pages 135–142.
3 Biljecki, F. and Ito, K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning, 215:104217.
4 Oliveira, W., Oliveira, D. D., and Braganholo, V. (2018). Provenance analytics for workflow-based computational experiments: A survey. ACM Comp. Surv., 51(3):53:1–53:25.
5 Fekete, J.-D. and Freire, J. (2020). Exploring reproducibility in visualization. IEEE Computer Graphics and Applications, 40(5):108–119.
6 Ferreira, N., Poco, J., Vo, H. T., Freire, J., and Silva, C. T. (2013). Visual exploration of big spatio-temporal urban data: A study of New York City taxi trips. IEEE TVCG, 19(12):2149–2158.
7 Heer, J., Bostock, M., and Ogievetsky, V. (2010). A tour through the visualization zoo. ACM Queue, 8(5):20–30.
8 Herschel, M., Diestelk¨amper, R., and Ben Lahmar, H. (2017). A survey on provenance: What for? what form? what from? VLDB J., 26(6):881–906.
9 Loibl, W., Vuckovic, M., Etminan, G., Ratheiser, M., Tschannett, S., and Osterreicher, D. (2021). Effects of densification on urban microclimate—a case study for the city of vienna. Atmosphere, 12(4).
10 Miranda, F., Hosseini, M., Lage, M., Doraiswamy, H., Dove, G., and Silva, C. T. (2020). Urban Mosaic: Visual exploration of streetscapes using large-scale image data. CHI ’20, page 1–15, New York, NY, USA.
11 Miranda, F., Ortner, T., Moreira, G., Hosseini, M., Vuckovic, M., Biljecki, F., Silva, C. T., Lage, M., and Ferreira, N. (2024). The state of the art in visual analytics for 3D urban data. Computer Graphics Forum, 43(3):e15112.
12 Moreira, G., Hosseini, M., Nipu, M. N. A., Lage, M., Ferreira, N., and Miranda, F. (2024). The Urban Toolkit: A grammar-based framework for urban visual analytics. IEEE TVCG, 30(1):1402–1412.
13 Moreira, G., Hosseini, M., Veiga, C., Alexandre, L., Colaninno, N., de Oliveira, D., Ferreira, N., Lage, M., and Miranda, F. (2025). Curio: A dataflow-based framework for collaborative urban visual analytics. IEEE TVCG, 31(1):1224–1234.
14 Oliveira, L. F., Oliveira, D., and Frota, Y. (2023). Defining routes for emergency response from climate events: a data-oriented approach. IEEE Latin Am. Trans., 21(10):1064–1072.
15 Psallidas, F. and Wu, E. (2018). Provenance for interactive visualizations. In Proceedings of the Workshop on Human-In-the-Loop Data Analytics, HILDA ’18, New York, NY, USA.
16 Satyanarayan, A., Moritz, D., Wongsuphasawat, K., and Heer, J. (2017). Vega-lite: A gram- mar of interactive graphics. IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis).
17 Sá, B. et al. (2021). Polroute-ds: um dataset de dados criminais para geração de rotas de patrulhamento policial. In DSW’21, pages 117–127. SBC.
18 Walchshofer, C., Hinterreiter, A., Xu, K., Stitz, H., and Streit, M. (2021). Provectories: Embedding-based analysis of interaction provenance data. IEEE TVCG).
19 Yu, B. and Silva, C. T. (2017). Visflow - web-based visualization framework for tabular data with a subset flow model. IEEE Transactions on Visualization and Computer Graphics, 23(1):251–260.