Towards semantically-aided domain specific business process modeling

Pages463-481
Published date04 September 2018
Date04 September 2018
DOIhttps://doi.org/10.1108/DTA-01-2018-0007
AuthorNikolaos Lagos,Adrian Mos,Mario Cortes-cornax
Subject MatterLibrary & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Metadata,Information & knowledge management,Information & communications technology,Internet
Towards semantically-aided
domain specific business
process modeling
Nikolaos Lagos and Adrian Mos
Naver Labs Europe, Meylan, France, and
Mario Cortes-cornax
Université Grenoble Alpes, Grenoble, France
Abstract
Purpose Domain-specific process modeling has been proposed in the literature as a solution to several
problems in business process management. The problems arise when using only the generic Business Process
Model and Notation (BPMN) standard for modeling. This language includes domain ambiguity and
difficult long-term model evolution. Domain-specific modeling involves developing concept definitions,
domain-specific processes and eventually industry-standard BPMN models. This entails a multi-layered
modeling approach, where any of these artifacts can be modified by various stakeholders and changes done
by one person may influence models used by others. There is therefore a need for tool support to keep track of
changes done and their potential impacts. The paper aims to discuss these issues.
Design/methodology/approach The authors use a multi-context systems-based approach to infer the
impacts that changes may cause in the models; and alsothe authors incrementally map components of
business process models to ontologies.
Findings Advantages of the framework include: identifying conflicts/inconsistencies across different
business modeling layers; expressing rich information on the relations between two layers; calculating the
impact of changes taking place in one layer to the rest of the layers; and selecting incrementally the most
appropriate semantic models on which the transformations can be based.
Research limitations/implications The authors consider this work as one of the foundational bricks
that will enable further advances toward the governance of multi-layer business process modeling systems.
Extensive usability tests would enable to further confirm the findings of the paper.
Practical implications The approach described here should improve the maintainability, reuse and
clarity of business process models and in extension improve data governance in large organizations.
The approaches described here should improve the maintainability, reuse and clarity of business process
models. This can improve data governance in large organizations and for large collections of processes by
aiding various stakeholders to understand problems with process evolutions, changes and inconsistencies
with business goals.
Originality/value This paper fulfills an identified gap to enabling semantically aided domainspecific
process modeling.
Keywords Business process management, Ontology, Domain-specific process modelling,
Multi-context systems, Multi-layer process, Semantic process modelling
Paper type Research paper
1. Introduction
Large organizations face a growing challenge of managing large collections of
heterogeneous business processes. The Business Process model and Notation (BPMN)
standard (Object Management Group, 2011) is used for modeling processes in a generic way.
BPMN brings several disadvantages such as domain ambiguity, long-term evolution and
limited reuse (Mos, 2014). Explicit semantics inherent to domain-specific models can
alleviate some of these disadvantages (Mos, 2014), providing effective means to deal with
application domains, improvements in expressiveness and ease of use (Mernik et al., 2005).
More specifically, it has been shown that domain-specific process modeling languages
(DSPML) can have significant advantages over BPMN (Mos and Cortes-Cornax, 2016).
However, domain-specific language development is hard, requiring both domain knowledge
and language development expertise (Mernik et al., 2005).
Data Technologies and
Applications
Vol. 52 No. 4, 2018
pp. 463-481
© Emerald PublishingLimited
2514-9288
DOI 10.1108/DTA-01-2018-0007
Received 15 January 2018
Revised 16 April 2018
Accepted 16 June 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2514-9288.htm
463
Domain specific
business process
modeling
Starting with concept definitions, designers can create domain-specific processes more
easily thanwith BPMN (Mos, 2014). From the aforementioned models,BPMN models can then
be generated and used in BPM Suites (BPMS) in order to be executed. The domain-specific
and BPMN layers may be connected via an intermediatelayer, which is responsible of taking
domain-specific modeling artifacts (process files, organizational structures) from a variety of
tools in their respective form and generating artifactsused by other tools (e.g. BPMN enabled
editors) (Mos and Jacquin, 2013). We refer tothis approach as Multi-layered Business Process
Modeling (MBPM) (Mos, 2014).
Governance in MBPM is difficult as different tools and formalisms can be
used for modeling processes. In addition, changes in one layer may influence models
used in the other layers. Changes that propagate to other layers are determined by the
transformation semantics between layers. Today, when looking at a large collection of
processes it is difficult for various stakeholders to understand problems with process
evolutions, changes and inconsistencies with business goals. There is a need for tool
support to detect inconsistencies, due to model updates happening in different layers.
There is also a need to address stakeholdersquestions based on their own perspectives
(business vs architect vs technical). In that respect, prior work did not consider using
specialized formalisms and reasoning engines tailored to different layers. The question
about how changes happening in one layer may influence the rest has not been treated
either. Furthermore, prior work in that domain did not consider easing the addition of
semantic information by incrementally selecting and adapting ontological models
according to the needs of the domain expert.
In this paper, previous work is extended by: formally defining MBPM systems in terms
of the knowledge represented in the various business modeling layers; describing how
business modeling artifacts in each layer can be transformed into semantic-based
representations, taking into account the specificities of each layer; framing the governance
of the semantic representations in a single integrated framework based on the multi-context
systems (MCS) framework (Brewka and Eiter, 2007), which supports the co-existence of
different formalisms, offering advanced inconsistency detection and querying capabilities
for improved governance, and introducing an incremental ontology selection and adaptation
approach based on feedback of the domain experts. The latter approach adapts ideas from
the field of ontology design patterns (ODPs). This paper is an extended version of work
initially presented in Lagos et al. (2017), notably with more detailed descriptions and the
introduction of a new method for incremental ontology selection and adaptation. More
generally, this work extends the field of semantic-based process modeling for multi-layered
business process management (BPM) systems.
The following paper is organized as follows. Section 2 illustrates the aforementioned
challenges tackled in this work. Section 3 includes a short overview of the basic
notions of MCSs and ODPs. Section 4 defines how MBPM layers can be transformed to
MCS contexts. Section 5 presents our approach to ontology selection and
construction. Section 6 presents how our contribution helps resolving the challenges
previously identified in Section 2. Related work and conclusions are presented in
Sections 7 and 8, respectively.
2. Problem description
MBPM systems include three different types of layers (Mos, 2014):aDSPMLlayerwherea
domain expert can design and model business processes and related information
(e.g. concepts); an Inter-Layer Connection Bridge (ILCB) layer that transforms the
information represented in the DSPML to models expressed in BPMN and vice-versa; and
the BPMN layer that includes the generated BPMN models. In that context, we have the
following challenges.
464
DTA
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