ProMoEE - A lightweight web editor supporting
study research on process models
Michael Winter∗[0000−0003−2561−7923], R¨udiger Pryss∗[0000−0003−1522−785X], and
Manfred Reichert∗[0000−0003−2536−4153]
* Institute of Databases and Information Systems, Ulm University, Ulm, Germany
(michael.winter,ruediger.pryss,manfred.reichert)@uni-ulm.de
Abstract. Process models are not only used for the sole documentation
of the numerous processes in an organization. Among others, they are
essential artifacts in the context of service-oriented computing. Hence,
high quality process models are the enabler for streamlining, prediction,
and automation in many fields (e.g., industrial production). Therefore,
a proper and effective comprehension of process models and knowledge
about factors influencing the creation of such models constitutes a key
criterion for this endeavor. The collection and analysis of data in scientific
studies help to understand the objective and subjective factors influen-
cing process model creation and comprehension. This work presents an
editor for the definition, execution, and analysis of studies in the context
of process model creation and comprehension. The editor features a clean
design and allows for a fast implementation for conducting and reporting
study research, while ensuring the collection of high-quality data.
Keywords: Study Research, Experimental Web Editor, Process Models
1 Introduction
Graphical workflows (i.e., process models) are key artifacts for the descriptive
representation of business tasks, logistical steps, or sophisticated algorithms. For
instance, as a centerpiece of the Business Process Management (BPM) domain
[7], it must be ensured that business process models are created and comprehen-
ded in such a way that practitioners can apply them correctly for their purposes.
Moreover, in the context of service-orientation, process models integrate a mul-
titude of essential functions, such as the definition of service mechanisms, allo-
cation of responsibilities, and the formulation of effective routines [2]. Research
on process models has unraveled numerous factors that influence the creation of
process models as well as factors fostering model comprehension [3]. However,
there are still many not known or not adequately known factors (e.g., especially
from a cognitive point of view) influencing the process model creation as well as
the comprehension. Consequently, it poses a challenge to bring those factors into
the light. One promising approach for coping with this challenge is to conduct
studies in order to develop a deeper understanding of the essential factors in
this context [9]. Following this, the work at hand presents the Process Modeling
2 Winter et al.
Experimental Editor (ProMoEE)1. ProMoEE is a lightweight web editor ena-
bling academics as well as professionals to get a swift, intuitive, and clean way
to conduct studies aiming at process model creation and comprehension. In the
long term, ProMoEE shall improve our general understanding of working with
process models in different domains (e.g., service-orientation).
The structure of this paper is as follows: Section 2 introduces ProMoEE. In
Section 3, related work is discussed and, finally, Section 4 summarizes the paper.
2 Process Modeling Experimental Editor
The emphasis of the Process Modeling Experimental Editor (ProMoEE) is to
foster study research on the creation as well as comprehension of process mo-
dels. Thereby, the editor supports the following three mandatory stages in study
research, i.e., Definition 1
,Execution 2
, and Analysis 3
.
Regarding Definition 1
, Fig. 1 presents the graphical user interface for the
definition of a study in ProMoEE. Thereby, the editor relies on the concept
of questionnaires. More specifically, a study and its progression are defined in a
structure known from questionnaires (see Fig 1(A)). Thereby, each questionnaire
contains an unique key to identify the correct study. A questionnaire has at least
one page (see Fig 1(B)) and a page can be defined with the following types:
Question,Comprehension, and Creation. In the Question section (see Fig 1(C)),
questions (e.g., demographics) can be created with different response options
(e.g., text field, single-/multi-choice). In the Comprehension section (see Fig
1(D)), a predefined process model expressed in terms of the Business Process
Model and Notation (BPMN) 2.0 is provided in order to evaluate the aspects
1Demonstration video of ProMoEE: https://tinyurl.com/y2hbvm99
Fig. 1. Definition of a Study in ProMoEE
Process Modeling Experimental Editor (ProMoEE) 3
of process model comprehension [5]. Therefore, specific questions emphasizing
model comprehension can be created to the user’s need. Finally, in the Creation
section, an environment is provided that allows for the creation of process models
in BPMN 2.0. In addition, a predefined process model can be specified in the
environment as well, which can be then adapted.
Regarding Execution 2
, to participate in a study, the unique key defined in
Definition 1
must be entered in the start screen. Here, as a major advantage,
ProMoEE can be accessed via web browser from anywhere with any computer
device (e.g., laptop, tablet). After entering the unique key, study participants
complete the study based on the defined questionnaire structure in Definition 1
.
Thereby, questions types like mandatory or restricted (e.g., integers only) ensure
that there are no missing or inconsistent values. Moreover, participants are able
to scroll (e.g., back) between the pages and, in case the study is canceled very
early, no data will be stored. At the end, participants are able to leave feedback.
In Analysis 3
, the originator of a study is able to analyze the obtained data
with a set of empirical and statistical methods. Therefore, all types of diffe-
rent data (e.g., timestamps) are stored in a database during the execution of
a study. In a specific analysis view, ProMoEE allows for a fine-grained analy-
sis; the obtained answers can be aggregated as well as visualized with different
techniques (e.g., pie chart). Moreover, on the created or comprehended process
models, numerous quantitative metrics as well as customized process model in-
spectors (e.g., syntactical compliance, semantic completeness) can be applied.
In addition, ProMoEE offers an export of data in an Excel file. Therefore, the
editor generates an adapted file (e.g., colored separation) for further usage in ot-
her applications (e.g., SPSS). Finally, ProMoEE includes an identity and access
management, in which three different account types can be utilized (i.e., Admin
A
,User B
, and Participant C
).
Altogether, ProMoEE supports research in the definition, execution, and ana-
lysis of studies in the context of process model creation as well as comprehension.
The editor provides a standardized and intuitive procedure for study research
to support academics or professionals in this context. For example, ProMoEE
mitigates threats towards data validity and pursues the collection of high-quality
data. Further, ProMoEE can be accessed with any computer device (e.g., smartp-
hone), only by the use of a web browser. Due to the use of latest technologies
(i.e., backend is implemented with PHP, frontend is implemented using current
web technologies), ProMoEE can be enriched with additional features. Finally,
the lightweight characteristics of ProMoEE allow for a fast and clean implemen-
tation as well as execution of studies. Generally, ProMoEE might be applied in
various studies to gain a better understanding of working with process models.
3 Related Work
Various tools exist for the implementation of studies that can be employed for
research on the creation and comprehension of process models. The Cheetah
Experimental Platform provides an experimental workflow for research investi-
4 Winter et al.
gating of the process of process modeling [6]. The authors in [8] demonstrate
a powerful configurator for designing studies, which, in turn, may also be used
for similar settings as ProMoEE. [1] presents a highly configurable smart mobile
device assessment tool that can be used for different visual tasks in the context
of process model comprehension. The application in [4] offers similar features for
collecting and sharing data from surveys. Summarizing, ProMoEE was develo-
ped for empirical research in the domain of BPM to study especially cognitive
aspects (e.g., decision-making) and, hence, none of the discussed approaches
combines such functionality with lightweight characteristics like ProMoEE does.
4 Summary and Outlook
This paper presented the Process Modeling Experimental Editor (ProMoEE)
empowering researchers to define, execute, and analyze studies in the context
of process model creation as well as comprehension in an intuitive, clean, and
fast manner. Thus, the insights obtained with ProMoEE may be used, inter
alia, to improve the business processes of an organization. Currently, ProMoEE
is used in different studies in order to evaluate user acceptance, usability, and
performance, especially in large-scale studies. Furthermore, ProMoEE is used in
various studies in the context of a conceptual framework to foster process model
comprehension from a cognitive viewpoint [10]. In future, ProMoEE will be
enriched with additional features (e.g., multi-process notation support), metrics,
and statistical methods (e.g., significance tests) to increase its applicability.
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