Sketch2BPMN: Automatic Recognition of Hand-Drawn BPMN Models

Bernhard Schäfer, Han van der Aa, Henrik Leopold, Heiner Stuckenschmidt

Veröffentlichungen: Beitrag in BuchBeitrag in KonferenzbandPeer Reviewed

Abstract

Despite the widespread availability of process modeling tools, the first version of a process model is often drawn by hand on a piece of paper or whiteboard, especially when several people are involved in its elicitation. Though this has been found to be beneficial for the modeling task itself, it also creates the need to manually convert hand-drawn models afterward, such that they can be further used in a modeling tool. This manual transformation is associated with considerable time and effort and, furthermore, creates undesirable friction in the modeling workflow. In this paper, we alleviate this problem by presenting a technique that can automatically recognize and convert a sketch process model into a digital BPMN model. A key driver and contribution of our work is the creation of a publicly available dataset consisting of 502 manually annotated, hand-drawn BPMN models, covering 25 different BPMN elements. Based on this data set, we have established a neural network-based recognition technique that can reliably recognize and transform hand-drawn BPMN models. Our evaluation shows that our technique considerably outperforms available baselines and, therefore, provides a valuable basis to smoothen the modeling process.

OriginalspracheEnglisch
TitelAdvanced Information Systems Engineering - 33rd International Conference, CAiSE 2021, Proceedings
Redakteure*innenMarcello La Rosa, Shazia Sadiq, Ernest Teniente
Herausgeber (Verlag)Springer Science and Business Media Deutschland GmbH
Seiten344-360
Seitenumfang17
ISBN (Print)9783030793814
DOIs
PublikationsstatusVeröffentlicht - 2021
Veranstaltung33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021 - Virtual, Online
Dauer: 28 Juni 20212 Juli 2021

Publikationsreihe

ReiheLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band12751 LNCS
ISSN0302-9743

Konferenz

Konferenz33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021
OrtVirtual, Online
Zeitraum28/06/212/07/21

ÖFOS 2012

  • 102015 Informationssysteme
  • 102003 Bildverarbeitung

Zitationsweisen