Minería de procesos e inteligencia artificial para el diseño, sostenibilidad y mejora de procesos colaborativos
Resumo
En las últimas décadas, la minería de procesos ha sido clave para mejorar procesos en las organizaciones. Hoy, la complejidad creciente, con procesos colaborativos que involucran múltiples actores, exige nuevas perspectivas de diseño y mejora. Al mismo tiempo, la sostenibilidad y la inteligencia artificial (IA) han cobrado protagonismo. Este trabajo doctoral busca ampliar el alcance de la minería de procesos y la IA, integrando técnicas, prácticas y herramientas para el diseño, sostenibilidad y mejora de procesos colaborativos.
Palavras-chave:
Minería de procesos, Procesos colaborativos, Sostenibilidad, Inteligencia artificial generativa
Referências
Berti, A., Kourani, H., Häfke, H., Li, C.-Y., and Schuster, D. (2024a). Evaluating large language models in process mining: Capabilities, benchmarks, and evaluation strategies. In Enterprise, Business-Process and Inf.Sys. Modeling, pages 13–21. Springer.
Berti, A., Schuster, D., and van der Aalst, W. M. P. (2024b). Abstractions, scenarios, and prompt definitions for process mining with llms: A case study. In Business Process Management Workshops, pages 427–439. Springer.
Brundtland, G. (1987). Report of the world commision on enviroment and development: our common future. In United Nations.
Calegari, D. and Delgado, A. (2023). A model-driven engineering perspective for the object-centric event data (oced) metamodel. In Int. Conf. on Business Process Management, pages 508–520. Springer.
Calero, C., Moraga, M. Á., and Piattini, M. (2021). Software Sustainability, pages 1–15. Springer.
Ceravolo, P., Comuzzi, M., De Weerdt, J., Di Francescomarino, C., and Maggi, F. M. (2024). Predictive process monitoring: concepts, challenges, and future research directions. Process Science, 1(1):2.
Corradini, F., Pettinari, S., Re, B., Rossi, L., and Tiezzi, F. (2024). A technique for discovering bpmn collaboration diagrams. Software and Systems Modeling, 23:1323–1343.
Couckuyt, D. and Looy, A. V. (2020). A systematic review of green business process management. Business Process Management Journal, 26(2):421–446.
Delgado, A., García, F., Moraga, M. Á., Calegari, D., Gordillo, A., and Peña, L. (2023). Adding the sustainability dimension in process mining discovery algorithms evaluation. In Business Process Management Forum, pages 163–177. Springer.
Di Francescomarino, C. and Ghidini, C. (2022). Predictive Process Monitoring, volume 448 of Lecture Notes in Business Information Processing, pages 320–346. Springer.
Fahland, D., Montali, M., Lebherz, J., van der Aalst,W. M. P., van Asseldonk, M., Blank, P., Bosmans, L., Brenscheidt, M., Ciccio, C. D., Delgado, A., Calegari, D., Peeperkorn, J., Verbeek, E., Vugs, L., and Wynn, M. T. (2024). Towards a simple and extensible standard for object-centric event data (OCED) - core model, design space, and lessons learned. CoRR, abs/2410.14495.
Genero Bocco, M., Piattini Velthuis, M. G., Cruz Lemus, J. A., and Díaz García, (2023). Métodos de investigación en informática. Ra-Ma.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014). Generative adversarial nets. Advances in neural information processing systems, 27.
Grohs, M., Abb, L., Elsayed, N., and Rehse, J.-R. (2024). Large language models can accomplish business process management tasks. In Business Process Management Workshops, pages 453–465. Springer.
Group, X. W. et al. (2016). Ieee standard for extensible event stream (xes) for achieving interoperability in event logs and event streams. IEEE Std, 1849:1–50.
Hernandez, J. D., Tello, E., Marin, H. M., Ramirez, U. M., and Mata, J. A. (2021). Merging event logs for inter-organizational process mining. In New Perspectives on Enterprise Decision-Making Applying AI Techniques, pages 3–26. Springer.
Hernández González, A., Calero, C., Pérez Parra, D., and Mancebo, J. (2019). Approaching green BPM characterisation. Journal of Software: Evolution and Process, 31(2).
Hevner, A. R., March, S. T., Park, J., and Ram, S. (2004). Design science in information systems research. MIS Q., 28(1):75–105.
István Koren, Janina Bauer, N. G. B. P. (2024). 1st international workshop on process mining for sustainability (pm4s). In Process Mining Workshops: ICPM 2024 International Workshops, Denmark, Revised Selected Papers.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Technical Report TR/SE-0401, Keele University and Empirical Soft. Eng. Joint Report, Keele, UK.
Kitchenham, B. A. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report, Keele, UK.
Kourani, H., Berti, A., Hennrich, J., Kratsch, W., Weidlich, R., Li, C.-Y., Arslan, A., Schuster, D., and van der Aalst, W. M. P. (2024). Leveraging large language models for enhanced process model comprehension. CoRR, abs/2408.08892.
Liu, C., Li, H., Zhang, S., Cheng, L., and Zeng, Q. (2023). Cross-department collaborative healthcare process model discovery from event logs. IEEE Transactions on Automation Science and Engineering, 20(3):2115–2125.
Mancebo, J., García, F., Pedreira, O., and Moraga, M. Á. (2017). Bpms-game: Tool for business process gamification. Business Process Management Forum, pages 127–140. Springer.
Parsifal (2025). Parsifal systematic review tool. Accessed: 2025-03-29.
Peña, L., Andrade, D., Delgado, A., and Calegari, D. (2024). An approach for discovering inter-organizational collaborative business processes in BPMN 2.0. In Process Mining Workshops, pages 487–498. Springer Nature Switzerland.
Rubio, M., Delgado, A., and Tansini, L. (2021). Process mining and data mining integration frameworks for evidence-based business intelligence: a systematic review. In 24th Iberoamerican Conf. on Software Engineering (CIbSE), pages 28–41. Curran Assoc.
Rubio, M., Delgado, A., and Tansini, L. (2023). An integrated approach to process and organizational data mining. In Latin American Computer Conf., pages 1–10. IEEE.
Schwartz, R., Dodge, J., Smith, N. A., and Etzioni, O. (2020). Green ai. Commun. ACM, 63(12):54–63.
Van Der Aalst, W. (2016). Green data science - using big data in an “environmentally friendly” manner. In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, pages 9–21. SciTePress.
van der Aalst, W. (2016). Process Mining: Data Science in Action, 2nd.ed. Springer.
van der Aalst, W. M. P. (2011). Intra- and inter-organizational process mining: Discovering processes within and between organizations. In The Practice of Enterprise Modeling, pages 1–11, Cham. Springer.
Venable, J. (2006). A framework for design science research activities. In Emerging Trends and Challenges in Information Technology Management, pages 184–187. Idea group publishing.
Weske, M. (2019). Business Process Management - Concepts, Languages, Architectures, 3rd Ed. Springer.
Wieringa, R. J. (2014). Design Science Methodology for Inf. Systems and Software Engineering. Springer.
Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th international conference on evaluation and assessment in software engineering, pages 1–10.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., and Regnell, B. (2012). Experimentation in Software Engineering. Springer.
Xu, L., Skoularidou, M., Cuesta-Infante, A., and Veeramachaneni, K. (2019). Modeling tabular data using conditional gan. Advances in neural information processing systems, 32.
Yin, R. K. (2014). Case Study Research: Design and Methods, 5th Ed. SAGE Publications, Inc.
Berti, A., Schuster, D., and van der Aalst, W. M. P. (2024b). Abstractions, scenarios, and prompt definitions for process mining with llms: A case study. In Business Process Management Workshops, pages 427–439. Springer.
Brundtland, G. (1987). Report of the world commision on enviroment and development: our common future. In United Nations.
Calegari, D. and Delgado, A. (2023). A model-driven engineering perspective for the object-centric event data (oced) metamodel. In Int. Conf. on Business Process Management, pages 508–520. Springer.
Calero, C., Moraga, M. Á., and Piattini, M. (2021). Software Sustainability, pages 1–15. Springer.
Ceravolo, P., Comuzzi, M., De Weerdt, J., Di Francescomarino, C., and Maggi, F. M. (2024). Predictive process monitoring: concepts, challenges, and future research directions. Process Science, 1(1):2.
Corradini, F., Pettinari, S., Re, B., Rossi, L., and Tiezzi, F. (2024). A technique for discovering bpmn collaboration diagrams. Software and Systems Modeling, 23:1323–1343.
Couckuyt, D. and Looy, A. V. (2020). A systematic review of green business process management. Business Process Management Journal, 26(2):421–446.
Delgado, A., García, F., Moraga, M. Á., Calegari, D., Gordillo, A., and Peña, L. (2023). Adding the sustainability dimension in process mining discovery algorithms evaluation. In Business Process Management Forum, pages 163–177. Springer.
Di Francescomarino, C. and Ghidini, C. (2022). Predictive Process Monitoring, volume 448 of Lecture Notes in Business Information Processing, pages 320–346. Springer.
Fahland, D., Montali, M., Lebherz, J., van der Aalst,W. M. P., van Asseldonk, M., Blank, P., Bosmans, L., Brenscheidt, M., Ciccio, C. D., Delgado, A., Calegari, D., Peeperkorn, J., Verbeek, E., Vugs, L., and Wynn, M. T. (2024). Towards a simple and extensible standard for object-centric event data (OCED) - core model, design space, and lessons learned. CoRR, abs/2410.14495.
Genero Bocco, M., Piattini Velthuis, M. G., Cruz Lemus, J. A., and Díaz García, (2023). Métodos de investigación en informática. Ra-Ma.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014). Generative adversarial nets. Advances in neural information processing systems, 27.
Grohs, M., Abb, L., Elsayed, N., and Rehse, J.-R. (2024). Large language models can accomplish business process management tasks. In Business Process Management Workshops, pages 453–465. Springer.
Group, X. W. et al. (2016). Ieee standard for extensible event stream (xes) for achieving interoperability in event logs and event streams. IEEE Std, 1849:1–50.
Hernandez, J. D., Tello, E., Marin, H. M., Ramirez, U. M., and Mata, J. A. (2021). Merging event logs for inter-organizational process mining. In New Perspectives on Enterprise Decision-Making Applying AI Techniques, pages 3–26. Springer.
Hernández González, A., Calero, C., Pérez Parra, D., and Mancebo, J. (2019). Approaching green BPM characterisation. Journal of Software: Evolution and Process, 31(2).
Hevner, A. R., March, S. T., Park, J., and Ram, S. (2004). Design science in information systems research. MIS Q., 28(1):75–105.
István Koren, Janina Bauer, N. G. B. P. (2024). 1st international workshop on process mining for sustainability (pm4s). In Process Mining Workshops: ICPM 2024 International Workshops, Denmark, Revised Selected Papers.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Technical Report TR/SE-0401, Keele University and Empirical Soft. Eng. Joint Report, Keele, UK.
Kitchenham, B. A. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report, Keele, UK.
Kourani, H., Berti, A., Hennrich, J., Kratsch, W., Weidlich, R., Li, C.-Y., Arslan, A., Schuster, D., and van der Aalst, W. M. P. (2024). Leveraging large language models for enhanced process model comprehension. CoRR, abs/2408.08892.
Liu, C., Li, H., Zhang, S., Cheng, L., and Zeng, Q. (2023). Cross-department collaborative healthcare process model discovery from event logs. IEEE Transactions on Automation Science and Engineering, 20(3):2115–2125.
Mancebo, J., García, F., Pedreira, O., and Moraga, M. Á. (2017). Bpms-game: Tool for business process gamification. Business Process Management Forum, pages 127–140. Springer.
Parsifal (2025). Parsifal systematic review tool. Accessed: 2025-03-29.
Peña, L., Andrade, D., Delgado, A., and Calegari, D. (2024). An approach for discovering inter-organizational collaborative business processes in BPMN 2.0. In Process Mining Workshops, pages 487–498. Springer Nature Switzerland.
Rubio, M., Delgado, A., and Tansini, L. (2021). Process mining and data mining integration frameworks for evidence-based business intelligence: a systematic review. In 24th Iberoamerican Conf. on Software Engineering (CIbSE), pages 28–41. Curran Assoc.
Rubio, M., Delgado, A., and Tansini, L. (2023). An integrated approach to process and organizational data mining. In Latin American Computer Conf., pages 1–10. IEEE.
Schwartz, R., Dodge, J., Smith, N. A., and Etzioni, O. (2020). Green ai. Commun. ACM, 63(12):54–63.
Van Der Aalst, W. (2016). Green data science - using big data in an “environmentally friendly” manner. In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, pages 9–21. SciTePress.
van der Aalst, W. (2016). Process Mining: Data Science in Action, 2nd.ed. Springer.
van der Aalst, W. M. P. (2011). Intra- and inter-organizational process mining: Discovering processes within and between organizations. In The Practice of Enterprise Modeling, pages 1–11, Cham. Springer.
Venable, J. (2006). A framework for design science research activities. In Emerging Trends and Challenges in Information Technology Management, pages 184–187. Idea group publishing.
Weske, M. (2019). Business Process Management - Concepts, Languages, Architectures, 3rd Ed. Springer.
Wieringa, R. J. (2014). Design Science Methodology for Inf. Systems and Software Engineering. Springer.
Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th international conference on evaluation and assessment in software engineering, pages 1–10.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., and Regnell, B. (2012). Experimentation in Software Engineering. Springer.
Xu, L., Skoularidou, M., Cuesta-Infante, A., and Veeramachaneni, K. (2019). Modeling tabular data using conditional gan. Advances in neural information processing systems, 32.
Yin, R. K. (2014). Case Study Research: Design and Methods, 5th Ed. SAGE Publications, Inc.
Publicado
12/05/2025
Como Citar
RUBIO, Martín.
Minería de procesos e inteligencia artificial para el diseño, sostenibilidad y mejora de procesos colaborativos. In: CONGRESSO IBERO-AMERICANO EM ENGENHARIA DE SOFTWARE (CIBSE), 28. , 2025, Ciudad Real/Espanha.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 312-319.
DOI: https://doi.org/10.5753/cibse.2025.35318.
