A mobile tool for recommending urban open data visualizations
Abstract
Tasks performed by government agencies produce exorbitant amounts of raw data daily. However, the value that these data could provide for society's different sectors can be lost if they are not properly collected and managed. Even with the adoption of data opening policies, institutions still face problems in the efficient use and interpretation of this data due to lack of training, appropriate tools, or cultural factors. In this work, we propose the construction of a mobile application to view data from the Open Data Portal in Recife. The application is based on an open data visualization recommendation framework, which can analyze the data types of the fields in a given data set to make the appropriate visualization type recommendation.
Keywords:
Data Visualization, Open Government Data, Data-Driven Public Management
References
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Macedo, D., Barcelos, R., Bernardini, F., and Viterbo, J. (2020). Uma ferramenta para recomendação de visualização de dados governamentais abertos. In ˜Anais do VIII Workshop de Computação Aplicada em Governo Eletrônico, pages 96–107. SBC.
Machado, V., Mantini, G., Viterbo, J., Bernardini, F., and Barcellos, R. (2018). An instrument for evaluating open data portals: A case study in brazilian cities. In Proceedings of the 19th Annual Inter Conf on Digital Government Research: Governance in the Data Age, pages 1–10.
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Nicholson-Crotty, S., Nicholson-Crotty, J., and Fernandez, S. (2017). Performance and management in the public sector: Testing a model of relative risk aversion. Public Administration Review, 77(4):603–614.
Paraskevopoulos, P., Dinh, T.-C., Dashdorj, Z., Palpanas, T., and Serafini, L. (2013). Identification and characterization of human behavior patterns from mobile phone data. D4D Challenge session, NetMob.
Qin, X., Luo, Y., Tang, N., and Li, G. (2018). Deepeye: An automatic big data visualization framework. Big data mining and analytics, 1(1):75–82.
Zuiderwijk, A. and Janssen, M. (2014). Open data policies, their implementation and impact: A framework for comparison. Government Information Quarterly, 31(1):17–29.
Barcellos, R., Viterbo, J., Bernardini, F., and Trevisan, D. (2018). An instrument for evaluating the quality of data visualizations. In 2018 22nd International Conference Information Visualisation (IV), pages 169–174.
Bernardini, F., Viterbo, J., Cappelli, C., and Berger, M. (2020). As cidades do futuro e a computação. In Maciel, C. and Viterbo, J., editors, Computação e Sociedade - Volume 2 - A Sociedade, chapter 11, pages 81–107. EdUFMT, Cuiaba. ´
Bommert, B. (2010). Collaborative innovation in the public sector. Inter public management review, 11(1):15–33.
Brandão, S. M. and Bruno-Faria, M. d. F. (2017). Barreiras à inovaçãao em gestão em organizações públicas do governo federal brasileiro: análise da percepção de dirigentes.
Cronholm, S., Gobel, H., and Rittgen, P. (2017). Challenges concerning data-driven innovation. In The 28th Australasian Conference on Information Systems, Hobart Australia, December 4-6, 2017.
Farazmand, A. et al. (2018). Global encyclopedia of public administration, public policy, and governance. Springer New York, NY.
Ferreira, B. (2019). Impulsionando inovação: novos designs para a gestão pública. Editora Bambual.
Foundation, O. K. (2015). Open data companion (odc) – bringing open data to the mobile platform. Available at https://okfnlabs.org/blog/2015/09/04/bringing-open-data-to-mobile.html.
Guenduez, A. A., Mettler, T., and Schedler, K. (2020). Technological frames in public administration: What do public managers think of big data? Government Information Quarterly, 37(1):101406.
Gurstein, M. B. (2011). Open data: Empowering the empowered or effective data use for everyone? First Monday.Jetzek, T., Avital, M., and Bjorn-Andersen, N. (2014). Data-driven innovation through open government data. Journal of theoretical and applied electronic commerce research, 9(2):100–120.
Jetzek, T., Avital, M., and Bjorn-Andersen, N. (2014). Data-driven innovation throughopen government data.Journal of theoretical and applied electronic commerce rese-arch, 9(2):100–120.
Keim, D. A., Mansmann, F., Schneidewind, J., and Ziegler, H. (2006). Challenges in visual data analysis. In Tenth Inter Conf on Information Visualisation (IV’06), pages 9–16. IEEE.
Kerr do Amaral, H. and Licio, E. C. (2008). O desenvolvimento de dirigentes como estratégia para o fortalecimento da capacidade de governo no Brasil: a experiência da ENAP. In XIII Congreso Internacional del CLAD.
Laudon, K. C., Laudon, J. P., et al. (2015). Management information systems. Pearson Upper Saddle River.
Lee, J., Kao, H.-A., and Yang, S. (2014). Service innovation and smart analytics for industry 4.0 and big data environment. Procedia Cirp, 16:3–8.
Macedo, D., Barcelos, R., Bernardini, F., and Viterbo, J. (2020). Uma ferramenta para recomendação de visualização de dados governamentais abertos. In ˜Anais do VIII Workshop de Computação Aplicada em Governo Eletrônico, pages 96–107. SBC.
Machado, V., Mantini, G., Viterbo, J., Bernardini, F., and Barcellos, R. (2018). An instrument for evaluating open data portals: A case study in brazilian cities. In Proceedings of the 19th Annual Inter Conf on Digital Government Research: Governance in the Data Age, pages 1–10.
Magnusson, J., Koutsikouri, D., and Paiv ¨ arinta, T. (2020). Efficiency creep and shadow innovation: enacting ambidextrous it governance in the public sector. European Journal of Information Systems, 29(4):329–349.
Mathis, K. (2015). Data-driven business models for service innovation in small and medium-sized businesses.
Mergel, I. (2018). Open innovation in the public sector: drivers and barriers for the adoption of challenge. gov. Public Management Review, 20(5):726–745.
Nicholson-Crotty, S., Nicholson-Crotty, J., and Fernandez, S. (2017). Performance and management in the public sector: Testing a model of relative risk aversion. Public Administration Review, 77(4):603–614.
Paraskevopoulos, P., Dinh, T.-C., Dashdorj, Z., Palpanas, T., and Serafini, L. (2013). Identification and characterization of human behavior patterns from mobile phone data. D4D Challenge session, NetMob.
Qin, X., Luo, Y., Tang, N., and Li, G. (2018). Deepeye: An automatic big data visualization framework. Big data mining and analytics, 1(1):75–82.
Zuiderwijk, A. and Janssen, M. (2014). Open data policies, their implementation and impact: A framework for comparison. Government Information Quarterly, 31(1):17–29.
Published
2021-07-18
How to Cite
VITÓRIO, Marcelo; BARCELLOS, Raissa; BERNARDINI, Flávia; VITERBO, José.
A mobile tool for recommending urban open data visualizations. In: LATIN AMERICAN SYMPOSIUM ON DIGITAL GOVERNMENT (LASDIGOV), 9. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 95-106.
ISSN 2763-8723.
DOI: https://doi.org/10.5753/wcge.2021.15980.
