From Acquisition to Interpretation: A Model for Creating Data Storytelling in Big Data
Resumo
Os procedimentos envolvidos nas etapas de planejamento, desenvolvimento e otimização de um projeto de Big Data apresentam desafios no escopo da Engenharia de Requisitos (RE), destacando as dificuldades inerentes ao gerenciamento de requisitos em equipes multidisciplinares. Otimizar as atividades relacionadas aos processos de requisitos e os processos que envolvem outras equipes, como a equipe de ciência de dados, contribui para o sucesso desses projetos. Este artigo apresenta um modelo para ajudar a criar data storytelling. O modelo abrange tudo, desde onde os dados são coletados, que tipo de visualização esses dados terão e como interpretar esse tipo de visualização.Referências
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Nalchigar, S., Yu, E., and Keshavjee, K. (2021). Modeling machine learning requirements from three perspectives: a case report from the healthcare domain. Requirements Engineering, 26:237–254.
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Zhang, Y., Reynolds, M., Lugmayr, A., Damjanov, K., and Hassan, G. M. (2022). A visual data storytelling framework. Informatics, 9(4).
Anderson, K. M. (2015). Embrace the challenges: Software engineering in a big data world. In 2015 ieee/acm 1st international workshop on big data software engineering, pages 19–25. IEEE.
Arruda, D. and Laigner, R. (2020). Requirements engineering practices and challenges in the context of big data software development projects: Early insights from a case study. In 2020 IEEE International Conference on Big Data (Big Data), pages 2012–2019. IEEE.
Arruda, D. and Madhavji, N. H. (2017). Towards a requirements engineering artefact model in the context of big data software development projects: Research in progress. In 2017 IEEE international conference on big data (big data), pages 2314–2319. IEEE.
Bosch, J., Olsson, H. H., and Crnkovic, I. (2018). It takes three to tango: Requirement, outcome/data, and ai driven development. In SiBW 2018, Software-intensive Business: Start-ups, Ecosystems and Platforms, Espoo, Finland, December 3, 2018, pages 177–192. CEUR-WS. org.
Costa, A. F., Freitas, L. I., Cavalcante, D. A., Oliveira, V. T., Lelli, V., Santos, I. S., Oliveira, P. A., Nogueira, T. P., and Andrade, R. M. (2024). Especificaçao de requisitos em um projeto de big data no setor publico. In Congresso Ibero-Americano em Engenharia de Software (CIbSE), pages 417–420. SBC.
Davoudian, A. and Liu, M. (2020). Big data systems: A software engineering perspective. 53(5).
Hull, E., Jackson, K., and Dick, J. (2005). Requirements engineering in the solution domain. Springer.
Lee, B., Choe, E. K., Isenberg, P., Marriott, K., and Stasko, J. (2020). Reaching broader audiences with data visualization. IEEE computer graphics and applications, 40(2):82–90.
Matei, S. A. and Hunter, L. (2021). Data storytelling is not storytelling with data: A framework for storytelling in science communication and data journalism. The Information Society, 37(5):312–322.
Nalchigar, S., Yu, E., and Keshavjee, K. (2021). Modeling machine learning requirements from three perspectives: a case report from the healthcare domain. Requirements Engineering, 26:237–254.
Nuseibeh, B. and Easterbrook, S. (2000). Requirements engineering: a roadmap. In Proceedings of the Conference on the Future of Software Engineering, pages 35–46.
Ren, P., Wang, Y., and Zhao, F. (2023). Re-understanding of data storytelling tools from a narrative perspective. Visual Intelligence, 1(1):11.
Van Vliet, H., Van Vliet, H., and Van Vliet, J. (2008). Software engineering: principles and practice, volume 13. John Wiley & Sons Hoboken, NJ.
Wheatcraft, L. S. and Ryan, M. J. (2018). Communicating requirements–effectively! In INCOSE International Symposium, volume 28, pages 716–732. Wiley Online Library.
Yasin, A., Liu, L., Cao, Z., Wang, J., Liu, Y., and Ling, T. S. (2018). Big data services requirements analysis. In Requirements Engineering for Internet of Things: 4th Asia-Pacific Symposium, APRES 2017, Melaka, Malaysia, November 9–10, 2017, Proceedings 4, pages 3–14. Springer.
Zhang, Y., Reynolds, M., Lugmayr, A., Damjanov, K., and Hassan, G. M. (2022). A visual data storytelling framework. Informatics, 9(4).
Publicado
20/07/2025
Como Citar
OLIVEIRA, Victória T.; ANDRADE, Rossana Maria de Castro; CASTRO, Miguel Franklin de; SANTOS, Ismayle S..
From Acquisition to Interpretation: A Model for Creating Data Storytelling in Big Data. In: LATIN AMERICAN SYMPOSIUM ON DIGITAL GOVERNMENT (LASDIGOV), 12. , 2025, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 227-236.
ISSN 2763-8723.
DOI: https://doi.org/10.5753/lasdigov.2025.9233.
