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A Semiotic Analysis of the Representativeness of BPMN Graphic Elements

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Business Modeling and Software Design (BMSD 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 483))

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Abstract

Business Process Modeling (BPM) has been under considerable attention from business and information technology (IT) communities. It is an important asset in the quest to decrease the gap in communication between these two groups. To contribute to decreasing this gap, this paper presents the execution of a quasi-experiment to verify whether Business Process Modelling Notation’s (BPMN) graphical elements are representative according to their semantics. Data collected with 89 participants, so far, through a semiotic analysis has shown that the notations’ elements are based on symbolic signs, understood due to shared law, while participants showed preference for iconic signs, that have visual relation to the real object.

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Acknowledgements

The authors would like to thank the NEPSI research group at UFPE for their support during this work, and CNPq (ref. 433419/2018-0) and FACEPE (ref. APQ-0867-6.02/22) for their financial support.

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Authors and Affiliations

  1. Federal University of Pernambuco, Recife, PE, Brazil

    Evelyne Batista Duarte & Denis Silva da Silveira

  2. University of Pernambuco, Recife, PE, Brazil

    Rafael Batista Duarte

Authors
  1. Evelyne Batista Duarte
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  2. Rafael Batista Duarte
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  3. Denis Silva da Silveira
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Corresponding author

Correspondence to Denis Silva da Silveira .

Editor information

Editors and Affiliations

  1. Bulgarian Academy of Sciences, University of Library Studies and Information Technologies, Sofia, Bulgaria

    Boris Shishkov

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Duarte, E.B., Duarte, R.B., da Silveira, D.S. (2023). A Semiotic Analysis of the Representativeness of BPMN Graphic Elements. In: Shishkov, B. (eds) Business Modeling and Software Design. BMSD 2023. Lecture Notes in Business Information Processing, vol 483. Springer, Cham. https://doi.org/10.1007/978-3-031-36757-1_14

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  • DOI: https://doi.org/10.1007/978-3-031-36757-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36756-4

  • Online ISBN: 978-3-031-36757-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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