Modelo de Apoio à Decisão para Avaliar Dados Governamentais Abertos do Setor Elétrico
Resumo
Este estudo propõe um modelo capaz de avaliar e priorizar, à luz dos critérios de riscos do contexto Open Government Data, dados do setor elétrico, apresentando os resultados via dashboards online interativos desenvolvido em R Shiny. A metodologia combina os métodos AHP e TOPSIS-2N, criando um ranking dos datasets conforme o seu nível de abertura. Os resultados apresentam o desempenho de cada conjunto de dados, exibindo aqueles que devem ser aprimorados em relação ao critérios de risco e aos temas priorizados.
Palavras-chave:
Modelo de Avaliação de Dados Abertos, AHP-TOPSIS-2N, Dados Abertos Governamentais (Conectados), Dados Abertos do Setor Elétrico, Modelo de Apoio à Decisão por Multicritérios
Referências
Ali-Eldin, A., Zuiderwijk-van Eijk, A., and Janssen, M. (2017). Opening more data: A new privacy risk scoring model for open data. In Proceedings of the 7th International Symposium on Business Modeling and Software Design 2017.
Araújo, I. P. (2022). Modelo de apoio à decisão para avaliar dados governamentais abertos do setor elétrico.
Belton, V. and Stewart, T. J. (2002). Multiple Criteria Decision Analysis:. Springer US.
Botchkarev, A. (2018). Towards a methodology of multi-criteria prioritization of open data for public release.
Buda, A., Ubacht, J., Janssen, M., and Sips, R.-J. (2015). Decision support framework for opening business data.
Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., Wirth, R., et al. (2000). Crisp-dm 1.0: Step-by-step data mining guide. SPSS inc, 9:13.
De Souza, L. P., Gomes, C. F. S., and De Barros, A. P. (2018). Implementation of new hybrid ahp-topsis-2n method in sorting and prioritizing of an it capex project portfolio. International Journal of Information Technology & Decision Making, 17(04):977–1005.
Eaves, D. (2009). The three laws of open government data.
Gerhardt, T. E. and Silveira, D. T. (2009). Métodos de pesquisa. Plageder.
Gutjahr, W. J. and Nolz, P. C. Multicriteria optimization in humanitarian aid. 252(2):351–366.
Hossain, M. A., Dwivedi, Y. K., and Rana, N. P. (2016). State-of-the-art in open data research: Insights from existing literature and a research agenda. Journal of organizational computing and electronic commerce, 26(1-2):14–40.
Hwang, C. and Yoon, K. (1981). Multiple attributes decision making methods and applications, spring. New York.
Kubler, S., Robert, J., Le Traon, Y., Umbrich, J. r., and Neumaier, S. (2016). Open data portal quality comparison using ahp. In Proceedings of the 17th International Digital Government Research Conference on Digital Government Research, pages 397–407. ACM, Association for Computing Machinery.
Luthfi, A. and Janssen, M. (2017). A conceptual model of decision-making support for opening data. In International Conference on e-Democracy, pages 95–105. Springer Verlag.
Luthfi, A. and Janssen, M. (2019). A comparative study of methods for deciding to open data. In International Symposium on Business Modeling and Software Design, pages 213–220. Springer.
Luthfi, A., Janssen, M., and Crompvoets, J. (2018a). A Causal Explanatory Model of Bayesian-belief Networks for Analysing the Risks of Opening Data, pages 289–297. Springer Verlag.
Luthfi, A., Janssen, M., and Crompvoets, J. (2018b). A framework for analyzing how governments open their data: Institution, technology, and process aspects influencing decision-making. EGOV-CeDEM-ePart 2018, page 163.
Luthfi, A., Janssen, M., and Crompvoets, J. (2019). Decision tree analysis for estimating the costs and benefits of disclosing data. In Conference on e-Business, e-Services and e-Society, pages 205–217. Springer.
Luthfi, A., Rehena, Z., Janssen, M., and Crompvoets, J. (2018c). A fuzzy multi-criteria decision making approach for analyzing the risks and benefits of opening data. In Conference on e-Business, e-Services and e-Society, pages 397–412. Springer Verlag.
Lyimo, N. N., Shao, Z., Ally, A. M., Twumasi, N. Y. D., Altan, O., and Sanga, C. A. (2020). A fuzzy logic-based approach for modelling uncertainty in open geospatial data on landfill suitability analysis. ISPRS International Journal of Geo-Information, 9(12):737.
Máchová, R. and Lněnička, M. (2019). A multi-criteria decision making model for the selection of open data management systems. Electronic Government, an International Journal, 15(4):372–391.
Mariano, A. M. and Santos, M. (2017). Revisão da literatura: apresentação de uma abordagem integradora. 18:427–442.
Martin, S. (2013). Risk analysis to overcome barriers to open data. Electronic Journal of e-Government, 11(2):pp348–359.
Palma, I., Ladeira, M., and Reis, A. C. B. (2021). Machine learning predictive model for the passive transparency at the brazilian ministry of mines and energy. In DG. O2021: The 22nd Annual International Conference on Digital Government Research, pages 76–81.
Parung, G. A., Hidayanto, A. N., Sandhyaduhita, P. I., Ulo, K. L. M., and Phusavat, K. (2018). Barriers and strategies of open government data adoption using fuzzy ahp-topsis: A case of indonesia. Transforming Government: People, Process and Policy.
Pfenninger, S., DeCarolis, J., Hirth, L., Quoilin, S., and Staffell, I. (2017). The importance of open data and software: Is energy research lagging behind? Energy Policy, 101:211–215.
Prodanov, C. C. and De Freitas, E. C. (2013). Metodologia do trabalho científico: métodos e técnicas da pesquisa e do trabalho acadêmico - 2ª edição.
Rafi, S., Yu, W., Akbar, M. A., Alsanad, A., and Gumaei, A. (2020). Multicriteria based decision making of devops data quality assessment challenges using fuzzy topsis. IEEE Access, 8:46958–46980.
Reis, A. C. B. and Schramm, V. B. (2022). Guia para aplicação da análise multicritério em análise de impacto regulatório (air) no inmetro. Projeto de Melhoria da Qualidade Regulatória - PN 15.2099.8-019.00, pages 21–30.
Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical modelling, 9(3-5):161–176.
Shaikh, S. A., Memon, M. A., Prokop, M., and Kim, K.-s. (2020). An ahp/topsis-based approach for an optimal site selection of a commercial opening utilizing geospatial data. In 2020 IEEE International Conference on Big Data and Smart Computing (BigComp), pages 295–302.
Worthy, B. (2015). The impact of open data in the uk: Complex, unpredictable, and political. 93(3):788–805.
Zopounidis, C. and Doumpos, M. (2017). Multiple Criteria Decision Making:. Springer.
Zuiderwijk, A. and Janssen, M. (2015). Towards decision support for disclosing data: Closed or open data? Information Polity, 20(2, 3):103–117.
Araújo, I. P. (2022). Modelo de apoio à decisão para avaliar dados governamentais abertos do setor elétrico.
Belton, V. and Stewart, T. J. (2002). Multiple Criteria Decision Analysis:. Springer US.
Botchkarev, A. (2018). Towards a methodology of multi-criteria prioritization of open data for public release.
Buda, A., Ubacht, J., Janssen, M., and Sips, R.-J. (2015). Decision support framework for opening business data.
Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., Wirth, R., et al. (2000). Crisp-dm 1.0: Step-by-step data mining guide. SPSS inc, 9:13.
De Souza, L. P., Gomes, C. F. S., and De Barros, A. P. (2018). Implementation of new hybrid ahp-topsis-2n method in sorting and prioritizing of an it capex project portfolio. International Journal of Information Technology & Decision Making, 17(04):977–1005.
Eaves, D. (2009). The three laws of open government data.
Gerhardt, T. E. and Silveira, D. T. (2009). Métodos de pesquisa. Plageder.
Gutjahr, W. J. and Nolz, P. C. Multicriteria optimization in humanitarian aid. 252(2):351–366.
Hossain, M. A., Dwivedi, Y. K., and Rana, N. P. (2016). State-of-the-art in open data research: Insights from existing literature and a research agenda. Journal of organizational computing and electronic commerce, 26(1-2):14–40.
Hwang, C. and Yoon, K. (1981). Multiple attributes decision making methods and applications, spring. New York.
Kubler, S., Robert, J., Le Traon, Y., Umbrich, J. r., and Neumaier, S. (2016). Open data portal quality comparison using ahp. In Proceedings of the 17th International Digital Government Research Conference on Digital Government Research, pages 397–407. ACM, Association for Computing Machinery.
Luthfi, A. and Janssen, M. (2017). A conceptual model of decision-making support for opening data. In International Conference on e-Democracy, pages 95–105. Springer Verlag.
Luthfi, A. and Janssen, M. (2019). A comparative study of methods for deciding to open data. In International Symposium on Business Modeling and Software Design, pages 213–220. Springer.
Luthfi, A., Janssen, M., and Crompvoets, J. (2018a). A Causal Explanatory Model of Bayesian-belief Networks for Analysing the Risks of Opening Data, pages 289–297. Springer Verlag.
Luthfi, A., Janssen, M., and Crompvoets, J. (2018b). A framework for analyzing how governments open their data: Institution, technology, and process aspects influencing decision-making. EGOV-CeDEM-ePart 2018, page 163.
Luthfi, A., Janssen, M., and Crompvoets, J. (2019). Decision tree analysis for estimating the costs and benefits of disclosing data. In Conference on e-Business, e-Services and e-Society, pages 205–217. Springer.
Luthfi, A., Rehena, Z., Janssen, M., and Crompvoets, J. (2018c). A fuzzy multi-criteria decision making approach for analyzing the risks and benefits of opening data. In Conference on e-Business, e-Services and e-Society, pages 397–412. Springer Verlag.
Lyimo, N. N., Shao, Z., Ally, A. M., Twumasi, N. Y. D., Altan, O., and Sanga, C. A. (2020). A fuzzy logic-based approach for modelling uncertainty in open geospatial data on landfill suitability analysis. ISPRS International Journal of Geo-Information, 9(12):737.
Máchová, R. and Lněnička, M. (2019). A multi-criteria decision making model for the selection of open data management systems. Electronic Government, an International Journal, 15(4):372–391.
Mariano, A. M. and Santos, M. (2017). Revisão da literatura: apresentação de uma abordagem integradora. 18:427–442.
Martin, S. (2013). Risk analysis to overcome barriers to open data. Electronic Journal of e-Government, 11(2):pp348–359.
Palma, I., Ladeira, M., and Reis, A. C. B. (2021). Machine learning predictive model for the passive transparency at the brazilian ministry of mines and energy. In DG. O2021: The 22nd Annual International Conference on Digital Government Research, pages 76–81.
Parung, G. A., Hidayanto, A. N., Sandhyaduhita, P. I., Ulo, K. L. M., and Phusavat, K. (2018). Barriers and strategies of open government data adoption using fuzzy ahp-topsis: A case of indonesia. Transforming Government: People, Process and Policy.
Pfenninger, S., DeCarolis, J., Hirth, L., Quoilin, S., and Staffell, I. (2017). The importance of open data and software: Is energy research lagging behind? Energy Policy, 101:211–215.
Prodanov, C. C. and De Freitas, E. C. (2013). Metodologia do trabalho científico: métodos e técnicas da pesquisa e do trabalho acadêmico - 2ª edição.
Rafi, S., Yu, W., Akbar, M. A., Alsanad, A., and Gumaei, A. (2020). Multicriteria based decision making of devops data quality assessment challenges using fuzzy topsis. IEEE Access, 8:46958–46980.
Reis, A. C. B. and Schramm, V. B. (2022). Guia para aplicação da análise multicritério em análise de impacto regulatório (air) no inmetro. Projeto de Melhoria da Qualidade Regulatória - PN 15.2099.8-019.00, pages 21–30.
Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical modelling, 9(3-5):161–176.
Shaikh, S. A., Memon, M. A., Prokop, M., and Kim, K.-s. (2020). An ahp/topsis-based approach for an optimal site selection of a commercial opening utilizing geospatial data. In 2020 IEEE International Conference on Big Data and Smart Computing (BigComp), pages 295–302.
Worthy, B. (2015). The impact of open data in the uk: Complex, unpredictable, and political. 93(3):788–805.
Zopounidis, C. and Doumpos, M. (2017). Multiple Criteria Decision Making:. Springer.
Zuiderwijk, A. and Janssen, M. (2015). Towards decision support for disclosing data: Closed or open data? Information Polity, 20(2, 3):103–117.
Publicado
29/05/2023
Como Citar
ARAÚJO, Ingrid Palma; REIS, Ana C. B..
Modelo de Apoio à Decisão para Avaliar Dados Governamentais Abertos do Setor Elétrico. In: CONCURSO DE TESES E DISSERTAÇÕES EM SISTEMAS DE INFORMAÇÃO - SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 19. , 2023, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 19-34.
DOI: https://doi.org/10.5753/sbsi_estendido.2023.229201.
