Abstract
The understandability of conceptual models depends not only on the model’s inner complexity and representation but also on the personal factors of the model’s audience. This is critical when conceptual models are used for achieving common ground during the early stages of requirements engineering for information systems and, moreover, for complex domains such as data protection. In this article, we present the results of an exploratory study consisting of eight focus groups with 21 experts on software development, business analysis and data protection, examining socio-technical models of an information system to identify privacy risks. We surveyed participants on their backgrounds to characterize the personal factors of understandability and performed an initial understandability assessment on a socio-technical model. We compared these values with the outcome of the focus group, i.e., the effectiveness of the participants in identifying privacy risks, annotating whether the risks are identified individually by a participant or collaboratively by two or more participants. The results suggest that most of the privacy risks were identified collaboratively, regardless of the previous understandability scores and personal factors such as experience and background.
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This article presents some partial results of Negri-Ribalta’s PhD thesis.
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References
Breaux, T.D., Norton, T.: Legal accountability as software quality: a US data processing perspective. In: 2022 IEEE 30th International Requirements Engineering Conference (RE). IEEE (2022)
Dalpiaz, F., Paja, E., Giorgini, P.: Security Requirements Engineering: Designing Secure Socio-Technical Systems. The MIT Press, Cambridge (2016)
Damian, D., Chisan, J.: An empirical study of the complex relationships between requirements engineering processes and other processes that lead to payoffs in productivity, quality, and risk management. IEEE Trans. Softw. Eng. 32 (2006)
Dikici, A., Turetken, O., Demirors, O.: Factors influencing the understandability of process models: a systematic literature review. Inf. Softw. Technol. 93, 112–129 (2018)
Engelsman, W., Wieringa, R.: Understandability of goal-oriented requirements engineering concepts for enterprise architects. In: Jarke, M., et al. (eds.) CAiSE 2014. LNCS, vol. 8484, pp. 105–119. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07881-6_8
Hadar, I., et al.: Privacy by designers: software developers’ privacy mindset. In: Proceedings of the 40th International Conference on Software Engineering, ICSE 2018. Association for Computing Machinery (2018)
Hadar, I., Reinhartz-Berger, I., Kuflik, T., Perini, A., Ricca, F., Susi, A.: Comparing the comprehensibility of requirements models expressed in use case and tropos: results from a family of experiments. Inf. Softw.Technol. 55, 1823–1843 (2013)
Houy, C., Fettke, P., Loos, P.: Understanding understandability of conceptual models – what are we actually talking about? In: Atzeni, P., Cheung, D., Ram, S. (eds.) ER 2012. LNCS, vol. 7532, pp. 64–77. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34002-4_5
Mendling, J., Djurica, D., Malinova, M.: Cognitive effectiveness of representations for process mining. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds.) BPM 2021. LNCS, vol. 12875, pp. 17–22. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85469-0_2
Moody, D.L.: The method evaluation model: a theoretical model for validating information systems design methods. In: Proceedings of the European Conference on Information Systems 2003. AIS Electronic Library (2003)
Negri-Ribalta, C., Noel, R., Herbaut, N., Pastor, O., Salinesi, C.: Socio-technical modelling for GDPR principles: an extension for the STS-ML. In: 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW) (2022)
Oliveira, F.F., Antunes, J.C., Guizzardi, R.S.: Towards a collaboration ontology. In: Proceedings of the Snd Brazilian Workshop on Ontologies and Metamodels for Software and Data Engineering, João Pessoa (2007)
Petrusel, R., Mendling, J., Reijers, H.A.: Task-specific visual cues for improving process model understanding. Inf. Softw. Technol. 79, 63–78 (2016)
Reijers, H.A., Mendling, J.: A study into the factors that influence the understandability of business process models. IEEE Trans. Syst. Man Cybern. - Part A: Syst. Hum. 41, 449–462 (2011)
Reijers, H.A., Mendling, J.: A study into the factors that influence the understandability of business process models. IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum. 41(3), 449–462 (2011)
Rumpe, B.: Agile modeling with the UML. In: Wirsing, M., Knapp, A., Balsamo, S. (eds.) RISSEF 2002. LNCS, vol. 2941, pp. 297–309. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24626-8_21
Stitzlein, C., Sanderson, P., Indulska, M.: Understanding healthcare processes. Proc. Hum. Factors Ergon. Soc. 57 (2013)
Sutcliffe, A.: User-Centred Requirements Engineering. Springer, Heidelberg (2002)
Vessey, I.: Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decis. Sci. 22(2) (1991)
Wang, W., Indulska, M., Sadiq, S., Weber, B.: Effect of linked rules on business process model understanding. In: Carmona, J., Engels, G., Kumar, A. (eds.) BPM 2017. LNCS, vol. 10445, pp. 200–215. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65000-5_12
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., Wesslén, A.: Experimentation in Software Engineering. Springer, Heidelberg (2012)
Yaqin, M.A., Sarno, R., Rochimah, S.: Measuring scalable business process model complexity based on basic control structure. Int. J. Intell. Eng. and Syst. 13, 52–65 (2020)
Acknowledgments
This work was supported by the Generalitat Valenciana through the CoMoDiD project (CIPROM/2021/023) and the Santiago Grisolía fellowship (GRISOLIAP/2020/096), and the Spanish State Research Agency through the DELFOS (PDC2021-121243-I00) and SREC (PID2021-123824OB-I00) projects.
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Velasquez, R., Negri-Ribalta, C., Noel, R., Pastor, O. (2023). Exploring Understandability in Socio-technical Models for Data Protection Analysis: Results from a Focus Group. In: Sales, T.P., Araújo, J., Borbinha, J., Guizzardi, G. (eds) Advances in Conceptual Modeling. ER 2023. Lecture Notes in Computer Science, vol 14319. Springer, Cham. https://doi.org/10.1007/978-3-031-47112-4_25
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