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A visual analysis of the process of process modeling

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Abstract

The construction of business process models has become an important requisite in the analysis and optimization of processes. The success of the analysis and optimization efforts heavily depends on the quality of the models. Therefore, a research domain emerged that studies the process of process modeling. This paper contributes to this research by presenting a way of visualizing the different steps a modeler undertakes to construct a process model, in a so-called process of process modeling Chart. The graphical representation lowers the cognitive efforts to discover properties of the modeling process, which facilitates the research and the development of theory, training and tool support for improving model quality. The paper contains an extensive overview of applications of the tool that demonstrate its usefulness for research and practice and discusses the observations from the visualization in relation to other work. The visualization was evaluated through a qualitative study that confirmed its usefulness and added value compared to the Dotted Chart on which the visualization was inspired.

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Notes

  1. An overview of these modeling sessions can be consulted at http://bpm.q-e.at/experiments.

  2. The only implementation of the Dotted Chart we are aware of, is the Dotted Chart Analysis plug-in in the process mining framework ProM.

  3. Note that this is only possible when there is a fixed, known set of possible occurring operations, which is the case in the study of the PPM.

  4. For readers that are familiar with process mining: this is the trace identifier in the event log.

  5. Due to a misalignment, this is not visible in a typical Dotted Chart without zooming in (this might be an unintentional bug).

  6. The PPMChart Analysis plug-in for ProM 6 can be downloaded at http://www.janclaes.info/plugins.php.

  7. The ProM tool can be downloaded at http://www.promtools.org.

  8. The xes file format of ProM is described at http://www.xes-standard.org.

  9. Both case descriptions can be downloaded from http://bpm.q-e.at/experiment/Pre-Flight.

  10. Case description can be downloaded from http://bpm.q-e.at/experiment/MortgageEindhoven.

  11. We are aware of the fact the models are unreadable. This does not prevent to judge the structure of the models. The process models can be downloaded in high resolution from http://www.janclaes.info/papers/PPMISeB.

References

  • Andrews K, Heidegger H (1998) Information slices: visualising and exploring large hierarchies using cascading, semi-circular discs. In: IEEE symposium on information visualization (Info Vis’98). IEEE computer society, Research Triangle Park, North Carolina, pp 9–12

  • Baird HS, Coates AL, Fateman RJ (2003) Pessimal print: a reverse turing test. Int J Doc Anal Recognit 5(2–3):158–163

    Article  Google Scholar 

  • Barros AP, Ter Hofstede AHM (1998) Towards the construction of workflow-suitable conceptual modelling techniques. Inf Syst J 8(4):313–337

    Article  Google Scholar 

  • Bertin J (2010) Semiology of graphics: diagrams, networks, maps. Economic & Social Research Institute, California, USA, p 438

  • Brown RA (2010) Conceptual modelling in 3D virtual worlds for process communication. In: Link S, Ghose A (eds) Proceeding APCCM’10 proceedings of the seventh Asia-pacific conference on conceptual modelling - volume 110. Australian Computer Society, Inc., Darlinghurst, pp 25–32

    Google Scholar 

  • Burch M, Beck F, Diehl S (2008) Timeline trees: visualizing sequences of transactions in information hierarchies. In: AVI’08 Proceedings of the working conference on advanced visual interfaces. ACM, New York, pp 75–82

  • Claes J, Vanderfeesten I, Reijers HA, Pinggera J, Weidlich M, Zugal S, Poels G (2012) Tying process model quality to the modeling process: the impact of structuring, movement, and speed. In: Barros A, Gal A, Kindler E (eds) Business process management. 10th international conference, BPM 2012, Tallinn, Estonia, September 3–6, 2012. Proceedings LNCS 7481. Springer, Berlin Heidelberg, pp 33–48

    Google Scholar 

  • Claes J, Vanderfeesten I, Pinggera J, Reijers HA, Weber B, Poels G (2013) Visualizing the process of process modeling with PPM Charts. In: La Rosa M, Soffer P (eds) Business process management workshops. BPM 2012 international workshops, Tallinn, Estonia, September 3, 2012. Revised papers. LNBIP 132. Springer, Berlin Heidelberg, pp 744–755

    Google Scholar 

  • Effinger P (2013) A 3D-navigator for business process models. In: La Rosa Marcello, Soffer P (eds.) Business process management workshops. BPM 2012 International Workshops, Tallinn, Estonia, September 3, 2012. Revised papers. LNBIP 132. Springer, Berlin Heidelberg, pp 737–743

  • Engelen L, Van den Brand M (2010) Integrating textual and graphical modelling languages. Electron Notes Theor Comput Sci 253(7):105–120

    Article  Google Scholar 

  • Gantt HL (1913) Work, wages, and profits, 2nd edn. Engineering Magazine Company, New York, p 312

  • Goodman N (1968) Languages of art: an approach to a theory of symbols. Hackett Publishing, USA 277

    Google Scholar 

  • Green DM, Swets JA (1966) Signal detection theory and psychophysics. John Wiley & Sons, USA, p 455

    Google Scholar 

  • Guo H, Brown RA, Rasmussen RK (2013) A theoretical basis for using virtual worlds as a personalised process visualisation approach. In: 2nd International workshop on human-centric information systems (p. (In Press))

  • Hahn J, Kim J (1999) Why are some diagrams easier to work with? Effects of diagrammatic representation on the cognitive integration process of systems analysis and design. ACM Trans Comput-Hum Interact 6(3):181–213

    Article  Google Scholar 

  • Hildebrandt T, Kriglstein S, Rinderle-Ma S (2012) Beyond visualization: on using sonification methods to make business processes more accessible to users. In: Nees MA, Walker BN, Freeman J (eds) Proceedings of the 18th international conference on auditory display, Atlanta, GA, USA, 18–21 June 2012. Georgia Institute of Technology, USA, pp 248–249

    Google Scholar 

  • Hoppenbrouwers SJBA, Proper HA, Van der Weide TP (2005) A fundamental view on the process of conceptual modeling. In: Delcambre L, Kop C, Mayr HC, Mylopoulos J, Pastor O (Eds.), Conceptual modeling: ER 2005. 24th international conference on conceptual modeling, Klagenfurt, Austria, October 24-28, 2005. Proceedings. LNCS 3716. Springer Berlin Heidelberg, USA, pp 128–143

  • Johnson B (1993) TreeMaps: visualizing hierarchical and categorical data

  • Johnson B, Shneiderman B (1991) Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: Visualization, 1991. Visualization’91, Proceedings, IEEE conference on. IEEE Comput Soc Press, pp 284–291)

  • Kaplan B, Maxwell J (2005) Qualitative research methods for evaluating computer information systems: impact of healthcare information systems, 30–55

  • Kim J, Hahn J, Hahn H (2000) How do we understand a system with (so) many diagrams? Cognitive integration processes in diagrammatic reasoning. Inf Syst Res 11(3):284–303

    Article  Google Scholar 

  • Larkin JH, Simon HA (1987) Why a diagram is (sometimes) worth ten thousand words. Cognit Sci 11(1):65–100

    Article  Google Scholar 

  • Lohse GL (1993) A cognitive model for understanding graphical perception. Hum Comput Interact 8(4):353–388

    Article  Google Scholar 

  • Mendling J, Recker JC, Reijers HA (2010a) On the usage of labels and icons in business process modeling. Int J Inf Syst Model Des 1(2):19

    Article  Google Scholar 

  • Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63(2):81–97

    Article  Google Scholar 

  • Moody DL (2009) The “Physics” of notations: toward a scientific basis for constructing visual notations in software engineering. Softw Eng IEEE Trans 35(6):756–779

    Article  Google Scholar 

  • Myers MD (1997) Qualitative research in information systems. MIS Q 21(2):241–242 MISQ Discovery, archival version, June 19

    Article  Google Scholar 

  • Mylopoulos J (1992) Conceptual modelling and telos. In: Loucopoulos P, Zicari R (eds) Conceptual modelling, databases and CASE: an integrated view of information systems development. John Wiley & Sons, Inc., New York, pp 1–20

    Google Scholar 

  • Neumann P (2005) Actress: visualizing relations in hierarchical data. In: Brodlie K, Duke D, Joy K (eds) Proceeding EUROVIS’05 proceedings of the seventh joint eurographics/IEEE VGTC conference on visualization. Eurographics Association Aire-la-Ville, Switzerland, pp 53–60

    Google Scholar 

  • Nordbotten JC, Crosby ME (1999) The effect of graphic style on data model interpretation. Inf Syst J 9(2):139–155

    Article  Google Scholar 

  • Norman DA (2002) The design of everyday things. Basic Books, New York, USA, p 257

  • Novak O (2002) Visualization of large graphs (study report). Czech Technical University, Prague, p 35

  • OMG (2011a) Business process model and notation (BPMN) version 2.0

  • OMG (2011b) Unified modeling language, superstructure (UML) version 2.4.1

  • Paivio A (1990) Mental representations. Oxford University Press, Oxford, p 324

    Book  Google Scholar 

  • Peffers K, Tuunanen T, Rothenberger MA, Chatterjee S (2007) A design science research methodology for information systems research. J Manage Inf Syst 24(3):45–77. doi:10.2753/MIS0742-1222240302

    Article  Google Scholar 

  • Phalp KT (1998) The CAP framework for business process modelling. Inf Softw Technol 40(13):731–744

    Article  Google Scholar 

  • Pinggera J, Zugal S, Weber B (2010) Investigating the process of process modeling with cheetah experimental platform. In: Mutschler B, Recker J, Wieringa R, Ralyte J, Plebani P (eds.), ER-POIS 2010. Proceedings of the 1st international workshop on empirical research in process-oriented information systems. CEUR WS Vol-603. CEUR-WS, pp 13–18

  • Pinggera J, Soffer P, Zugal S, Weber B, Weidlich M, Fahland D, Mendling J (2012) Modeling styles in business process modeling. In: Bider I, Halpin T, Krogstie J, Nurcan S, Proper E, Schmidt R, Wrycza S (eds.), Enterprise, business-process and information systems modeling. 13th International conference, BPMDS 2012, 17th international conference, EMMSAD 2012, and 5th eurosymposium, held at CAiSE 2012, Gdańsk, Poland, June 25–26, 2012. Proceedings. LNBIP 113. Springer, pp 151–166

  • Pinggera J, Zugal S, Weidlich M, Fahland D, Weber B, Mendling J, Reijers HA (2012) Tracing the process of process modeling with modeling phase diagrams. In: Daniel F, Barkaoui K, Dustdar S (eds.), Business process management workshops. BPM 2011 international workshops, Clermont-Ferrand, France, August 29, 2011, Revised selected papers, part I. LNBIP 99 (Vol. LNBIP 99). Springer Berlin Heidelberg, pp 370–382

  • Pinggera J, Furtner M, Martini M, Sachse P, Katharina R, Zugal S, Weber B (2013) Investigating the process of process modeling with eye movement analysis. In: La Rosa Marcello, Soffer P (Eds.), Business process management workshops. BPM 2012 International workshops, Tallinn, Estonia, September 3, 2012. Revised papers. LNBIP 132. Springer, Berlin Heidelberg, pp 438–450

  • Pinggera J, Soffer P, Fahland D, Weidlich M, Zugal S, Weber B, Mendling J (2013) Styles in business process modeling: an exploration and a model. Softw Syst Model (accepted)

  • Polyvyanyy A (2012) Structuring process models

  • Polyvyanyy A, Smirnov S, Weske M (2010) Business process model abstraction. In: Vom Brocke J, Rosemann M (eds.), Handbook on business process management 1. Introduction, methods, and information systems. Part II. Springer, Berlin Heidelberg, pp 149–166

  • Quinlan PT (2003) Visual feature integration theory: past, present, and future. Psychol Bull 129(5):643–673

    Article  Google Scholar 

  • Reichert M (2013). Visualizing large business process models: challenges, techniques, applications. In: La Rosa Marcello, Soffer P (eds.), Business process management workshops. BPM 2012 International Workshops, Tallinn, Estonia, September 3, 2012. Revised papers. LNBIP 132. Springer, Berlin Heidelberg, pp 725–736

  • Reisig W, Rozenberg G (1998) Lectures on petri nets I: basic models, advances in petri nets, LNCS 1491. Springer, Berlin Heidelberg, p 681

    Google Scholar 

  • Scheer A-W (1998) Business process engineering: reference models for industrial enterprises. Springer-Verlag, Germany, p 757

    Google Scholar 

  • Song M, Van der Aalst WMP (2007) Supporting process mining by showing events at a glance. In Chari K, Kumar A (eds.), Proceeding of the seventeenth annual workshop on information technologies and systems (WITS’07). pp 139–145

  • Stasko JT, Zhang E (2000) Focus + context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations. In: Information visualization, 2000. IEEE symposium on (Vol. 2000). IEEE Comput Soc Press, pp 57–65

  • Thompson MM, Naccarato ME, Parker KE (1989) Assessing cognitive need: the development of the personal need for structure and personal fear of invalidity scales. In Annual meeting of the Canadian Psychological Association, Halifax

    Google Scholar 

  • Treisman AM (1982) Perceptual grouping and attention in visual search for features and for objects. J Exp Psychol Hum Percept Perform 8(2):194–214

    Article  Google Scholar 

  • Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cogn Psychol 12(1):97–136

    Article  Google Scholar 

  • Tufte ER (1983) The visual display of quantitative information. Graphics Press, USA 197

    Google Scholar 

  • Van der Aalst WMP (1998) The application of petri nets to workflow management. J Circuit Syst Comput 8(1):21–66

    Article  Google Scholar 

  • Van der Aalst WMP (2011) Process mining: discovery, conformance and enhancement of business processes. Springer, Heidelberg, p 352

    Book  Google Scholar 

  • Van der Aalst WMP, Ter Hofstede AHM (2005) YAWL: yet another workflow language. Inf Syst 30(4):245–275

    Article  Google Scholar 

  • Van Dongen BF, De Medeiros AKA, Verbeek HMW, Weijters AJMM, Van der Aalst WMP (2005) The ProM framework: a new era in process mining tool support. In: Ciardo G, Darondeau P (eds.), Applications and theory of petri nets. 26th international conference, ICATPN 2005, Miami, USA, June 20–25, 2005. Proceedings. LNCS 3536. Springer, Berlin Heidelberg, pp 444–454

  • Vessey I, Galletta D (1991) Cognitive fit: an empirical study of information acquisition. Inf Syst Res 2(1):63–84

    Article  Google Scholar 

  • Weber R (1997) Ontological foundations of information systems. Coopers & Lybrand, Melbourne, Victoria, Australia, p 212

  • Weber B, Pinggera J, Zugal S, Wild W (2010) Handling events during business process execution: an empirical test. In: Mutschler B, Recker J, Wieringa R (eds.), Proceedings of the 1st international workshop on empirical research in process-oriented information systems (ER-POIS’10). CEUR-WS, pp 19–30

  • Weidlich M, Zugal S, Pinggera J, Weber B, Reijers HA, Mendling J (2010) The impact of change task type on maintainability of process models. In: Mutschler B, Recker J, Wieringa R (Eds.), Proceedings of the 1st international workshop on empirical research in process-oriented information systems (ER-POIS’10). CEUR-WS, pp 1–12

  • Weijters AJMM, Van der Aalst WMP (2001) Process mining: discovering workflow models from event-based data. In: Kröse B, De Rijke M, Schreiber G, Van Someren M (eds.), Proceedings of the 13th Belgium-Netherlands conference on artificial intelligence (BNAIC 2001). pp 283–290

  • Weske M (2007) Business process management: concepts, languages, architectures. Springer, Berlin, Heidelberg, p 372

    Google Scholar 

  • Wilson JM (2003) Gantt charts: a centenary appreciation. Eur J Oper Res 149(2):430–437

    Article  Google Scholar 

  • Winn W (1990) Encoding and retrieval of information in maps and diagrams. IEEE Trans Prof Commun 33(3):103–107

    Article  Google Scholar 

  • Winn W (1993) An account of how readers search for information in diagrams. Contemp Educ Psychol 18(2):162–185

    Article  Google Scholar 

  • Fekete JD, Van Wijk JJ, Stasko JT, North C (2008) The value of information visualization. In: Kerren A, Stasko JT, Fekete J-D, North C (eds.), Information visualization. Human-centered issues and perspectives. LNCS 4950. Springer, Berlin Heidelberg, pp 1–18

  • Zur Muehlen M, Recker JC (2008) How much language is enough? Theoretical and practical use of the business process modeling notation. In: Bellahsène Z, Léonard M (eds.), Advanced information systems engineering. 20th international conference, CAiSE 2008 Montpellier, France, June 16–20, 2008 proceedings. LNCS 5074. Springer Berlin, Heidelberg, pp 465–479

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Acknowledgments

Our research builds upon the work of the development team of CEP and the researchers involved in the modeling sessions. Therefore, we express our extensive gratitude to Stefan Zugal, Jan Mendling and Dirk Fahland. We also thank the various people that provided feedback on the plug-in, subjects of the initial experiments and participants of the qualitative evaluation study. This research was funded by the Austrian Science Fund (FWF): P23699-N23.

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Authors and Affiliations

  1. Ghent University, FEB08, Tweekerkenstraat 2, 9000, Ghent, Belgium

    Jan Claes & Geert Poels

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Jan Claes, Irene Vanderfeesten & Hajo A. Reijers

  3. University of Innsbruck, Innsbruck, Austria

    Jakob Pinggera & Barbara Weber

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  1. Jan Claes
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  2. Irene Vanderfeesten
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  3. Jakob Pinggera
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  4. Hajo A. Reijers
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  5. Barbara Weber
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Correspondence to Jan Claes.

Appendix: Parameter settings of the PPM Chart analysis plug-in in ProM

Appendix: Parameter settings of the PPM Chart analysis plug-in in ProM

1.1 Configuration

At the left hand side, the view can be configured (see Fig. 5 in the paper).

The Component type indicates which dimension is used to define the unit of the timelines. In contrast to the Dotted Chart Analysis plug-in, this option cannot be configured. The fixed value for this option in the PPMChart implementation is:

  • Model element (default): select this option to view a timeline per model element. Each dot on the timeline represents an operation on the model element represented by the timeline (e.g., create, move, (re)name, delete of a particular XOR gateway).

The Time option can be configured to zoom in on the timing of the operations. Next three options can be selected:

  • Actual (default): select this option to view the dots positioned according to the real time of execution of the corresponding operation.

  • Relative (Time): select this option to shift every time line in such a way that the first operation on each line is set to the beginning of the time interval of the PPM Chart.

  • Relative (Ratio): select this option to stretch every timeline in such a way that the first operation on each line is set to the beginning of the time interval and the last operation on each line is set to the end of the time interval (if at least two operations exist on the line).

Vertical time intervals are marked according to the Time intervals configuration parameter. There are 13 different options.

  • L-1, L-10, L-100, L-500: select these options to divide the chart in time intervals of 1, 10, 100, or 500 ms respectively. Time intervals are indicated with white vertical lines starting at the time of the first operation in the chart. It is necessary to zoom in on the chart to be able to analyze the chart at millisecond level.

  • Seconds, Minutes, Half hours, Hours (default): select these options to divide the chart in time intervals of seconds, minutes, half hours, or hours respectively.

  • Days, Week, Months, Years: select these options to divide the chart in time intervals of days, weeks, months, or years respectively. It is necessary to zoom out on the chart to be able to analyze the chart at a level >1 h.

The option Color by indicates if the dots have to be color-coded or not. The PPM Chart in principle uses a fixed default color coding (if turned on), but the colors can be changed by the user in the Settings tab (see Appendix section “Settings”). Next two options can be selected:

  • None: select this option to remove color coding. Each dot will have the same color, which allows the user to focus on shape and position of the dots (in order to abstract from the type of operation).

  • Operation (default): select this option to apply color coding. By default, create operations will be colored in green, move operations in blue, delete operations in red, and (re)naming in orange. A detailed legend of the default colors is displayed in Table 3.

    Table 3 Default color (shade) and shape coding of events
    Full size table

Use the Shape by setting to configure if the dots have to be shape-coded or not. The PPM Chart in principle uses a fixed default shape coding (if turned on), but the shapes can be changed by the user in the Settings tab (see Appendix section “Settings”). Next two options can be selected:

  • None: select this option to turn off dot shaping. Each dot will be displayed as a circle, which allows the user to focus on color and position of dots (to abstract from the model element type of the operation).

  • Model element (default): select this option to turn on dot shaping. Operations on activities will be displayed with rectangles, event operations with circles, gateway operations with diamonds, and edges with triangles. A detailed shape legend is displayed in Table 3.

Sort by can be used to influence the order in which the timelines are sorted (vertically). If descending is selected, the sort order is reversed. Next eight options can be selected:

  • None: select this option to select no ordering. The order of the data in the event log will be used.

  • Model element: select this option to sort the lines by the model element identifier. The lines will be sorted according to the identifiers of the model elements represented by the timelines.

  • Number of operations: select this option to sort the lines by the number of operations displayed on each line. Use this option to graphically observe differences between lines with fewer operations (top part of the chart if sorted according to this option) and lines with more operations (bottom part of the chart).

  • Duration: select this option to sort the lines according to their duration. The duration is defined as the time span between the first and the last operation on the line. This option allows to compare lines with shorter versus longer durations.

  • Distance from start (default): select this option to sort the lines according to the traversing order of the corresponding model elements from the start event towards the end event (see description in Sect. 3.4.4 of the paper).

  • Create order from start: select this option to sort the lines according to the logical order of creation of the corresponding elements from start event to end event (see description in Sect. 3.4.4 of the paper).

  • First operation: select this option to sort the lines according to the time of the operation of the first dot on the line. This option facilitates to zoom in on the actual order of creation of model elements.

  • Last operation: select this option to sort the lines according to the time of the operation represented by the last dot on the line. This option facilitates to zoom in on parts of the process model that are (not) touched towards the end of the modeling process.

Configure the Mouse mode to set the way the mouse behaves in the plug-in. Next three options can be selected:

  • Select (default): select this option to be able to select different dots. Click on a dot or make a rectangular selection to indicate of which dots to display information in a tooltip.

  • Zoom in: select this option to be able to easily zoom in on parts of the PPM Chart. Make a rectangular selection on the screen to indicate the area you want to zoom in on.

  • Drag: select this option to be able to bring a different area of the chart into the displayed rectangle if zoomed in. Drag the chart under the displayed rectangle to show other parts of the chart.

The sliders zoom (X) and zoom (Y) can be used to zoom in horizontal or vertical dimension respectively on a logarithmical scale. The Zoom out button restores the zoom level to 1 × 1. The Update button needs to be pressed after changing one or more of previous options before the PPM Chart is repainted on the screen.

1.2 Filtering

At the right-hand side the user can customize the view by filtering on specific operations or model elements (see Fig. 5 in the paper). The top part represents a small view on the unfiltered PPM Chart. Below, one can configure next three filter options:

  • Hide next model elements: choose to hide specific element types (e.g., hide edges). All dots that represent operations on an element of the selected type are removed from the chart. However, no timelines are removed. This might result in a PPM Chart with a number of empty timelines (i.e., without any dot on the line).

  • Hide next operations: choose to hide specific operation types (e.g., hide (re)name operations). All dots that represent operations of the selected types are removed from the chart. Again, only dots are removed from the chart, not timelines. Empty timelines may originate from this option if the model element represented by the timeline has only operations that are selected to be hidden.

  • Hide all elements with these operations: hide elements with a specific operation (e.g., hide deleted elements). All dots that represent any operation on a model element that contains at least one operation of the selected operation type are removed from the chart. Again, only dots are removed from the chart, not timelines.

1.3 Settings

Use the Settings tab page to change the color and shape coding of elements. Simply click on the button to change the color or shape for the corresponding operation.

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Claes, J., Vanderfeesten, I., Pinggera, J. et al. A visual analysis of the process of process modeling. Inf Syst E-Bus Manage 13, 147–190 (2015). https://doi.org/10.1007/s10257-014-0245-4

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