A study of different visualizations for visualizing differences in process models

Manuel Gall, Günter Wallner, Simone Kriglstein, Stefanie Rinderle-Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Finding differences between two processes can be a complex, time consuming, and expensive task. Our work is based on the difference graph approach which calculates the differences between two process models and – if available – their instances. In this paper we evaluate different possibilities for visualizing these differences. For this purpose we have selected some common visual properties such as color, shape, and size and evaluated these different visualizations with 31 participants through an online survey. Our results show that color coding and symbols were the preferred methods of the participants for depicting differences in a graph visualization.

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9382
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference34th International Conference on Conceptual Modeling, ER 2015 and held with in Conceptual Modeling for Ambient Assistance and Healthy Ageing, AHA 2015, Conceptual Modeling of Services, CMS 2015, Event Modeling and Processing in Business Process Management, EMoV 2015, Modeling and Management of Big Data, MoBiD 2015, Modeling and Reasoning for Business Intelligence, MORE-BI 2015, Conceptual Modeling in Requirements Engineering and Business Analysis, MReBA 2015, Quality of Modeling and Modeling of Quality, QMMQ 2015, Symposium on Conceptual Modeling Education, SCME 2015
Country/TerritorySweden
CityStockholm
Period19/10/1522/10/15

Keywords

  • Difference graph
  • Instance flow
  • Process differences
  • Process model
  • Visualization

Fingerprint

Dive into the research topics of 'A study of different visualizations for visualizing differences in process models'. Together they form a unique fingerprint.

Cite this