Visual Analytics Research at Universidade Federal do Ceará
Resumo
In this paper, we describe the research in visual analytics that is a partnership between two research groups at the Federal University of Ceara, CRAB – Computer Graphics, Virtual Reality, Animation, and Visualization Group and Insight Data Science Lab. This fruitful collaboration joined CRAB’s expertise in Visualization with Insight Lab’s expertise in Data Science to bring about valuable research and development projects in the public and private sector in many areas, including crime analysis, mobility data visualization, education, and games. We briefly describe our main projects in these areas and their social, technological, and scientific contributions in the following sections.
Referências
R. S. Lima, S. Bueno, B. Rodrigues, A. C. Pekny, L. Figueiredo, P. N. Pröglhöf, I. Sobral, V. Moneo, C. A. P. Aparício, T. Kahn, C. Ricardo, D. Cerqueira, F. L. Oliveira, F. S. Silva, L. Pires, L. O. Ramos, L. G. Cunha, M. F. Baird, M. F. T. Peres, N. Pollachi, R. Alcadipani, R. Custódio, R. Miki, R. Muggah, and U. Peres, “Anuário brasileiro de segurança pública 2014,” São Paulo, SP, Brazil, Tech. Rep., 2014. [Online]. Available: http://www.forumseguranca.org.br/storage/8n_anuarion_2014n_20150309.pdf
C. Izique, “Crescimento da violência no país surpreende pesquisadores,” São Paulo, SP, Brazil, 2013. [Online]. Available: https://exame.com/brasil/violencia-democracia-e-direitos-humanos/
J. F. d. Q. Neto, E. Santos, and C. A. Vidal, “Mskde - using marching squares to quickly make high quality crime hotspot maps,” in 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2016, pp. 305–312.
J. F. de Queiroz Neto, E. Santos, C. A. Vidal, and D. S. Ebert, “A visual analytics approach to facilitate crime hotspot analysis,” Computer Graphics Forum, vol. 39, no. 3, pp. 139–151, 2020. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13969
A. R. C. Ramos, E. Santos, and J. B. Cavalcante-Neto, “A partition approach to interpolate polygon sets for animation,” in 2019 32nd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2019, pp. 139–146.
F. C. F. N. Junior, T. L. C. d. Silva, J. F. d. Q. Neto, J. A. F. d. Macêdo, and W. C. Porcino, “A novel approach to approximate crime hotspots to the road network,” in Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility, ser. PredictGIS’19. New York, NY, USA: Association for Computing Machinery, 2019, p. 53–61. [Online]. Available: https://doi.org/10.1145/3356995.3364538
S. P. Chainey, J. A. S. Matias, F. C. F. Nunes Junior, T. L. Coelho da Silva, J. A. F. de Macêdo, R. P. Magalhães, J. F. de Queiroz Neto, and W. C. P. Silva, “Improving the creation of hot spot policing patrol routes: Comparing cognitive heuristic performance to an automated spatial computation approach,” ISPRS International Journal of Geo-Information, vol. 10, no. 8, 2021. [Online]. Available: https://www.mdpi.com/2220-9964/10/8/560
J. F. de Queiroz Neto, “A visual analytics approach for geocoded crime data,” Ph.D. dissertation, Federal University of Ceara, Fortaleza, CE, Brazil, 4 2020.
HINT.FM. (2012) Wind map. [Online]. Available: https://hint.fm/wind
G. A. M. Gomes, E. Santos, and C. A. Vidal, “Interactive visualization of traffic dynamics based on trajectory data,” in 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2017, pp. 111–118.
G. A. Gomes, E. Santos, C. A. Vidal, T. L. C. da Silva, and J. A. F. Macedo, “Real-time discovery of hot routes on trajectory data streams using interactive visualization based on gpu,” Computers & Graphics, vol. 76, pp. 129 – 141, 2018. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0097849318301420
G. Andrienko, N. Andrienko, U. Demsar, D. Dransch, J. Dykes, S. I. Fabrikant, M. Jern, M.-J. Kraak, H. Schumann, and C. Tominski, “Space, time and visual analytics,” International Journal of Geographical Information Science, vol. 24, no. 10, pp. 1577–1600, 2010.
A. J. M. Leite, E. Santos, C. A. Vidal, and J. A. F. D. Macêdo, “Visual analysis of predictive suffix trees for discovering movement patterns and behaviors,” in 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2017, pp. 103–110.
C. L. Rocha, I. R. Brilhante, F. Lettich, J. A. F. De Macedo, A. Raffaetà, R. Andrade, and S. Orlando, “TPRED: a Spatio-Temporal Location Predictor Framework,” in Proceedings of the 20th International Database Engineering & Applications Symposium. ACM, 2016, pp. 34–42.
R. L. L. e. Silva Filho, P. R. Motejunas, O. Hipólito, and M. B. D. C. M. Lobo, “A evasão no ensino superior brasileiro,” Cadernos de Pesquisa, vol. 37, no. 132, pp. 641–659, 2007. [Online]. Available: [link].
A. M. Barbosa, E. Santos, and J. P. P. Gomes, “A machine learning approach to identify and prioritize college students at risk of dropping out,” in XXVIII Simpósio Brasileiro de Informática na Educação SBIE (Brazilian Symposium on Computers in Education), Recife, Nov 2017, pp. 1497–1506.
C. Anuradha and T. Velmurugan, “A data mining based survey on student performance evaluation system,” 5th IEEE International Conference on Computational Intelligence and Computing Research, IEEE ICCIC 2014, no. December 2014, pp. 43–47, 2015. [Online]. Available: [link].
A. M. Barbosa, A. N. de Araujo Neto, E. Santos, and J. P. P. Gomes, “Using learning analytics and visualization techniques to evaluate the structure of higher education curricula,” in XXVIII Simpósio Brasileiro de Informática na Educação SBIE (Brazilian Symposium on Computers in Education), Recife, Nov 2017, pp. 1297–1306.
P. Hinrichs, “The effects of affirmative action bans on college enrollment, educational attainment, and the demographic composition of universities,” The Review of Economics and Statistics, vol. 94, no. 3, pp. 712–722, 2012. [Online]. Available: http://dx.doi.org/10.1162/REST a 00170
A. Abadie, A. Diamond, and J. Hainmueller, “Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program,” Journal of the American Statistical Association, vol. 105, no. 490, pp. 493–505, 2010. [Online]. Available: http://dx.doi.org/10.1198/jasa.2009.ap08746
A. J. M. L. Junior, E. Santos, C. A. Vidal, and C. L. Rocha, “Empregando Análise Visual e Sensemaking no Ensino de Predictive Suffix Trees,” in XXIX Simpósio Brasileiro de Informática na Educação SBIE (Brazilian Symposium on Computers in Education), Fortaleza, Nov 2018, pp. 1043– 1052.
A. S. Bastos, E. Santos, G. A. M. Gomes, and M. A. Mourão, “Evaluating the Use of Affordable User Testing and Visualization Techniques in Level Design of a Hardcore 2D Platform Game,” in XVIII SBGames - Art & Design Track, Rio de Janeiro, Oct 2019, pp. 145–154.
C. Izique, “Crescimento da violência no país surpreende pesquisadores,” São Paulo, SP, Brazil, 2013. [Online]. Available: https://exame.com/brasil/violencia-democracia-e-direitos-humanos/
J. F. d. Q. Neto, E. Santos, and C. A. Vidal, “Mskde - using marching squares to quickly make high quality crime hotspot maps,” in 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2016, pp. 305–312.
J. F. de Queiroz Neto, E. Santos, C. A. Vidal, and D. S. Ebert, “A visual analytics approach to facilitate crime hotspot analysis,” Computer Graphics Forum, vol. 39, no. 3, pp. 139–151, 2020. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13969
A. R. C. Ramos, E. Santos, and J. B. Cavalcante-Neto, “A partition approach to interpolate polygon sets for animation,” in 2019 32nd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2019, pp. 139–146.
F. C. F. N. Junior, T. L. C. d. Silva, J. F. d. Q. Neto, J. A. F. d. Macêdo, and W. C. Porcino, “A novel approach to approximate crime hotspots to the road network,” in Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility, ser. PredictGIS’19. New York, NY, USA: Association for Computing Machinery, 2019, p. 53–61. [Online]. Available: https://doi.org/10.1145/3356995.3364538
S. P. Chainey, J. A. S. Matias, F. C. F. Nunes Junior, T. L. Coelho da Silva, J. A. F. de Macêdo, R. P. Magalhães, J. F. de Queiroz Neto, and W. C. P. Silva, “Improving the creation of hot spot policing patrol routes: Comparing cognitive heuristic performance to an automated spatial computation approach,” ISPRS International Journal of Geo-Information, vol. 10, no. 8, 2021. [Online]. Available: https://www.mdpi.com/2220-9964/10/8/560
J. F. de Queiroz Neto, “A visual analytics approach for geocoded crime data,” Ph.D. dissertation, Federal University of Ceara, Fortaleza, CE, Brazil, 4 2020.
HINT.FM. (2012) Wind map. [Online]. Available: https://hint.fm/wind
G. A. M. Gomes, E. Santos, and C. A. Vidal, “Interactive visualization of traffic dynamics based on trajectory data,” in 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2017, pp. 111–118.
G. A. Gomes, E. Santos, C. A. Vidal, T. L. C. da Silva, and J. A. F. Macedo, “Real-time discovery of hot routes on trajectory data streams using interactive visualization based on gpu,” Computers & Graphics, vol. 76, pp. 129 – 141, 2018. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0097849318301420
G. Andrienko, N. Andrienko, U. Demsar, D. Dransch, J. Dykes, S. I. Fabrikant, M. Jern, M.-J. Kraak, H. Schumann, and C. Tominski, “Space, time and visual analytics,” International Journal of Geographical Information Science, vol. 24, no. 10, pp. 1577–1600, 2010.
A. J. M. Leite, E. Santos, C. A. Vidal, and J. A. F. D. Macêdo, “Visual analysis of predictive suffix trees for discovering movement patterns and behaviors,” in 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Oct 2017, pp. 103–110.
C. L. Rocha, I. R. Brilhante, F. Lettich, J. A. F. De Macedo, A. Raffaetà, R. Andrade, and S. Orlando, “TPRED: a Spatio-Temporal Location Predictor Framework,” in Proceedings of the 20th International Database Engineering & Applications Symposium. ACM, 2016, pp. 34–42.
R. L. L. e. Silva Filho, P. R. Motejunas, O. Hipólito, and M. B. D. C. M. Lobo, “A evasão no ensino superior brasileiro,” Cadernos de Pesquisa, vol. 37, no. 132, pp. 641–659, 2007. [Online]. Available: [link].
A. M. Barbosa, E. Santos, and J. P. P. Gomes, “A machine learning approach to identify and prioritize college students at risk of dropping out,” in XXVIII Simpósio Brasileiro de Informática na Educação SBIE (Brazilian Symposium on Computers in Education), Recife, Nov 2017, pp. 1497–1506.
C. Anuradha and T. Velmurugan, “A data mining based survey on student performance evaluation system,” 5th IEEE International Conference on Computational Intelligence and Computing Research, IEEE ICCIC 2014, no. December 2014, pp. 43–47, 2015. [Online]. Available: [link].
A. M. Barbosa, A. N. de Araujo Neto, E. Santos, and J. P. P. Gomes, “Using learning analytics and visualization techniques to evaluate the structure of higher education curricula,” in XXVIII Simpósio Brasileiro de Informática na Educação SBIE (Brazilian Symposium on Computers in Education), Recife, Nov 2017, pp. 1297–1306.
P. Hinrichs, “The effects of affirmative action bans on college enrollment, educational attainment, and the demographic composition of universities,” The Review of Economics and Statistics, vol. 94, no. 3, pp. 712–722, 2012. [Online]. Available: http://dx.doi.org/10.1162/REST a 00170
A. Abadie, A. Diamond, and J. Hainmueller, “Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program,” Journal of the American Statistical Association, vol. 105, no. 490, pp. 493–505, 2010. [Online]. Available: http://dx.doi.org/10.1198/jasa.2009.ap08746
A. J. M. L. Junior, E. Santos, C. A. Vidal, and C. L. Rocha, “Empregando Análise Visual e Sensemaking no Ensino de Predictive Suffix Trees,” in XXIX Simpósio Brasileiro de Informática na Educação SBIE (Brazilian Symposium on Computers in Education), Fortaleza, Nov 2018, pp. 1043– 1052.
A. S. Bastos, E. Santos, G. A. M. Gomes, and M. A. Mourão, “Evaluating the Use of Affordable User Testing and Visualization Techniques in Level Design of a Hardcore 2D Platform Game,” in XVIII SBGames - Art & Design Track, Rio de Janeiro, Oct 2019, pp. 145–154.
Publicado
18/10/2021
Como Citar
SANTOS, Emanuele; NETO, José F. de Queiroz; GOMES, George A. M.; LEITE JUNIOR, Antonio José M.; CAVALCANTE NETO, Joaquim Bento; VIDAL, Creto Augusto; SILVA, Ticiana L. Coelho da; MACEDO, Jose Antonio F..
Visual Analytics Research at Universidade Federal do Ceará. In: WORKSHOP DE VISUAL ANALYTICS, VISUALIZAÇÃO DE INFORMAÇÕES E CIENTÍFICA - CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 34. , 2021, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 248-251.
DOI: https://doi.org/10.5753/sibgrapi.est.2021.20048.
