Mariam Keriakos, Hoda Hosny and Sherif G. Aly
Department of Computer Science and Engineering, The American University in Cairo,
Road 109, New Cairo, Egypt
Keywords: Business Process Management, Context Awareness, Decision Making, Aspectization of Contextual
Abstract: Informed decision making and flexibility have grown to be important standard requirements in the field of
business process modeling and design due to the emergence of intrinsically complex variables within the
various business environments. Traditionally, researches on business process modeling and informed
decision making have focused on the configurability of business process models. Our review of literature
makes us confident that researches have considerably neglected the main drivers of flexibility and decision-
making which have an extensive impact on business process flow. Such drivers form, in our opinion, cross
cutting concerns that need to be extracted from the context of business processes. Context can include, but is
not limited to, work force availability, work force experience, system failures, weather conditions,
environmental hazards, and financial constraints. This paper presents a new general purpose methodology
for modeling the context of business processes within different business domains as Open Aspects, and
accordingly, deducing recommendations for improving the business process flow. We envision how context
can be conceptualized as Open Aspects, how to classify the different contextual aspects into different
business operational levels according to the goals of the business processes, and how to present business
process flow recommendations based on the aspectized contextual facts.
Business process modeling has been an important
area of research for a number of years due to the
need for simulating and automating business
processes in the software industry. The flexibility of
business processes has been a strong motivation for
many researches as it offers a means to make
business process models both configurable and
adaptive. Flexibility is defined as the capability to
change without loss of identity (Regev, Bider and
Wegmann, 2007). The need for business process
flexibility stems from the variance in the context of
application of the same business process. The
context of a process is basically defined as the
surrounding conditions of a business process that
cause alteration in its behavior (Rosemann, Recker
and Flender, 2008). These surrounding conditions or
“context” may be viewed as a collection of cross
cutting concerns which affect the decisions that
should be taken and hence directly affect the
business process flow and may enforce certain key
decisions or customizations on the business model.
The changes that are made throughout the process
lifecycle can be wider than just changes in the
process flow. Adopting context awareness and
advanced context modeling; representing context in
terms of aspects are therefore critical for process
change strategies. Despite, the growing importance
of the business process context and the advantages
of its aspectization, it has not yet drawn researchers’
attention. Most researches involving context
awareness focused on pervasive systems and mobile
computing. So far neither the aspectization of
business process nor contextual business items in
general have been considered. In this research we
focus on modeling business process context (as
aspects) within the business processes. Our aim is to
enrich the field of business process modeling by
taking advantage of context modeling and
aspectization for more effective decision making
within the business processes.
The rest of the paper is organized as follows:
section 2 discusses the research problem and
motivation, section 3 summarizes the research
background of this work, section 4 describes our
high level solution approach, section 5 demonstrates
an example and section 6 concludes the paper.
Keriakos M., Hosny H. and G. Aly S..
DOI: 10.5220/0003905702060213
In Proceedings of the 2nd International Conference on Pervasive Embedded Computing and Communication Systems (PECCS-2012), pages 206-213
ISBN: 978-989-8565-00-6
2012 SCITEPRESS (Science and Technology Publications, Lda.)
With the growing number of variables and concerns
involved in the decision-making process of any
sizable business, designing and adapting business
processes is becoming a very complicated task.
Within the business domain, concerns surrounding
the environment where the processes are executed
give indications that are essential for a business
process-related decision. For example if a certain
airline company knows that there is a high
probability of weather problems on a specific day,
this would normally affect the business processes of
take-off and landing and if there is a problem in
check-in counters, this would very likely change the
behavior of the check-in process. If the context of a
business process is aspectized and modeled
efficiently, this will provide a stronger cause-effect
relationship between the demands for process
flexibility and their impact on processes and vice
versa (Rosemann, Recker and Flender, 2008).
Hence, the business processes would be able to
automatically change their behavior as if decision
makers were present to analyze the situation and
give an immediate solution. For more complex
problems where human intervention is a must,
knowing the aspects that are affected would help
decision-makers better analyze the situation and take
important decisions which would save time, effort
and money. Representing context variables as
aspects is an important addition to the world of
business process modeling and context awareness
for the following reasons:
1) Modularization of contextual elements/items to
allow for reuse of same context elements in
different kinds of business process and in
different business domains
2) The dynamic nature offered by the open
Aspects concept of the adaptation model. This
allows the weaving of events and
advices/actions to happen at run time which is
most appropriate for the dynamic environments
in which most business processes run
3) The concept of aspects/cross cutting concerns is
more appealing to business people and business
process experts than the idea of a process, in
business process management, away from the
world of computing and software. Business
decision-makers always consider aspects before
making a decision but the term and idea of
context is more distant from the business world
Today many business process modeling and
management frameworks/tools exist, but they do not
adequately support the context-based definition and
configuration of business process variants. As a
result, the process of adaptation of business
processes in such tools is time consuming and error
prone (Hallerbach, Bauer and Reichert, 2008). In the
current business process modeling tools, the process
models are disconnected from the relevant context in
which they are valid and there is often no
traceability to the situation in which the process
should take place (Rosemann, Recker and Flender,
As a result, the decisions related to changes in
the flow of a business process are taken manually
and usually at a late stage after identifying a major
contextual variance in the environment of the
business process. This could lead to faulty decision-
making due to contextual ignorance or right
decision-making at a late stage, and in both cases,
the outcome is degraded efficiency in the business
process management and consequently unnecessary
financial costs which could be avoided. In this
research work, we propose a new methodology that
enables business process experts to model context-
aware, aspectized and configurable business
processes which change their flow and decision
according to contextual information obtained from
the ambient surrounding of the business process
environment. Our solution approach is to extend an
existing context awareness framework by adding
Open Aspects for business contextual elements
apriori then use the aspectual facts modeled as
decision making criteria for business process
modelers to add context intelligence to the modelers.
Our research contribution mainly extends on two
major research domains, namely: Aspect oriented
software development (AOSD) and context
awareness. We integrate with another area of
research which is business process modeling by
introducing aspectized context awareness. We are
not the first to discuss the idea of context within
business process modeling as it has been discussed
as a high level concept by Rosemann et al (2008, pp.
3-4) but we do introduce the idea of conceptualizing
business process context in terms of aspects and we
define the idea of a solution that extends on existing
frameworks of both context awareness and business
process modeling to realize the new approach of
aspectized context aware business processes. In this
section we summarize the theories, approaches, tools
and concepts which served as the basis for our work.
3.1 Aspect Orientation
Aspect oriented software development (AOSD) is a
relatively new emerging technology and
methodology (Chavez, Garcia, and Lucena, 2001;
Tarr and Ossher, 2000). The general purpose of
AOSD is the modularization of crosscutting
concerns. However, researches in AOSD focused
mainly on concerns related to logging, tracing,
debugging, security and program verification
(Kiczales, 2001; Anon, Microsoft Researches in
Cross Cutting Concerns, 2011; Anon, Microsoft
Enterprise Library, 2011) and little research was
done on aspectization of scenario based
requirements modeling (Whittle and Araujo, 2004).
Other crucial areas of research like business process
modeling and context awareness which incorporate
cross cutting concerns have yet to be discovered.
Open Aspects is a new approach for mitigating
unplanned changes in systems based on aspect-
oriented composition at run time (Hirschfeld and
Hanenberg, 2006). Open aspects support the so
called adaptation models system change events
being observed and the corresponding corrective
actions to be taken. The main motivation behind
open aspects is the flexibility to change, at runtime,
the aspect composition according to the base system
and the set of aspects that it is applied to. There is a
clear separation of base, aspect and adaptation
models. In open aspects the weaver derives a model
of the running base system needed for making the
aspect model effective (both marked with a ‘start’
tag). While doing so, the weaver examines an
adaptation model (also marked with a ‘start’ tag)
detailing all involved system change events to be
observed and all corrective actions to be taken in
correspondence to the system elements involved.
3.2 Context Awareness State of Art
Context awareness exists in many other disciplines
other than business process modeling and has
received much attention in these areas e.g. Web-
based systems (Kaltz, Ziegler and Lohmann, 2005),
Mobile applications (Mikalsen and Petersen, 2004)
and conceptual modeling (Analyti, Theodorakis,
Spyratos, and Constantopoulos, 2007; Rolland,
Souveyet and Achour, 1998). In the computing
domain, the term ‘context-aware’ was coined by
Schilit and Theimer (1994, pp.5-6) as approaches to
incorporating contextual factors into various
systems, such as in the area of Mobile applications.
They typically focus on users and their interaction
with the systems (Dey, 2001; Schilit and Theimer,
1994). Existing frameworks (such as the ECOIN
framework (Firat, Madnick, and Manola,
2005))attempt to represent context as properties that
can be interpretation-based either on the inbuilt
framework structures or based on a generic ontology
that has no structure prior to design time. Almost all
context-aware frameworks currently available in the
market and even developed for research purpose
were coined within the field of pervasive systems
and its applications (e.g. smart hospitals and smart
homes). The main problem with most of these
context-aware frameworks is that they are focused
on pervasive systems and mobile entities, that they
lack customization for context of business processes
and that they are not open source so their usage or
extension must be under the supervision of their
3.3 Context Description and Structure
Context structuring and linking context to real
causes is a prerequisite to context conceptualization
within the business process modeling discipline. A
substantial amount of research has already been
conducted on structuring and describing context. In
the area of context modeling, for example, there is
the form of context ontology (Chen, Finin, and
Joshi, 2003). In another effort, the Context Ontology
Language (Strang, Linnhoff-Popien, and Frank,
2003) is designed to accommodate selected aspects
of context such as temperature, scales, the relative
strengths of aspects and further metadata.
Rosemann (2008, pp.3-4) identifies an onion
model for structuring contextual elements related to
a business process. Rosemann widens the scope of
contextual elements consideration to include
environmental context (related to the economy or the
general environment where the business process
operates) as well as immediate context elements
(which directly affect the flow of a business
process). The Rosemann onion model is the basis of
the context model structure that we adopted within
our research work. Rosemann (2008, pp.3-4) divides
the context into four disjoint categories as follows
1) Immediate Context: includes those elements that
go beyond the constructs that constitute the pure
control flow, and covers those elements that
directly facilitate the execution of a process.
2) Internal Context: The immediate system (viz.
the process) which is embedded in the wider
system of an organization. Various elements of
an organization have indirect influence on a
PECCS 2012 - International Conference on Pervasive and Embedded Computing and Communication Systems
business process and he calls this second layer,
the internal context.
3) External Context: Compromises the elements
that are outside the organization control but
reside within the business network where the
organization operates (Parkinson and Baker,
4) Environmental Context: This is the outermost
layer and it captures the overall environment as
a system with comprehensive boundaries.
3.4 Context Modelling Techniques
Context modeling techniques have been the focus of
research in the last few years. Most of the techniques
were designed for use in pervasive systems and
ubiquitous computing while a few techniques were
targeted for requirements modeling and process
modeling. In this section we discuss some of the
most relevant models to our methodology and
research on modeling context related to business
Rolland et al. (1998, pp.6-7) suggested a context-
oriented procedure based on objectives to identify
requirements chunks in goal-based modeling. Their
basic idea for determining goals and relevant context
in a model is based on the notion of a requirement
chunk, which is a pair < Goal, Scenario > and
denotes a potential way for achieving a goal within a
given scenario (i.e. one instantiation of the process).
Rosemann et al (2008, pp.6-7) define a goal-
oriented process modeling approach to be able to
identify relevant contextual elements. The
granularity and scope of a business process model is
closely linked to the goals of the depicted process.
By examining why a process exists and what the
objectives and goals of the process are, the context
factors that pose relevance to the process can be
predetermined and modeled at a formal level over
and above the typical description levels of
organization, data, resource and IT (Jablonski and
Bussler, 1996; Scheer, 2000).
Nurcan and Saidani (2009, pp. 5-6) introduced a
context model for BPM (CM4BPM) and a role-
based business process model (RBPM). They
presented an approach allowing the enactment of
processes with respect to context. Nurcan and
Saidani (2009, pp. 5-6) presents an approach for
business process (BP) modeling which supports the
explicit definition of the context-related knowledge
in order to make instance adaptations "context-
aware". The approach consists of using contextual
knowledge in order to enhance the adequacy and the
coherence of the assignments during the enactment
of the business processes, such as actor-to-role or
process-to role assignments. In order to efficiently
use the contextual information in business process
enactment rules, they suggest that context related
knowledge (CRK) should be formally defined.
We evaluated and compared the above
mentioned context modeling techniques (Table 1)
according to the following criteria:
1) Quality of contextual information (QC): this
criterion measures the quality of modeling the
contextual information as sensed by various
types of sensors which varies with time and
depends on how accurately the model reflects
the real contextual facts.
2) Formality (FR): this criterion measures the
levels of understandability, standardization,
preciseness and traceability of contextual facts.
3) Ease of use (EU): this criterion measures how
easy it is for industry/business experts to
understand the context model and the contextual
facts and to map them to real business aspects
for a better decision making process.
4) Adaptability/Change tolerance (AC): this
criterion measures the flexibility of the context
model to change by incorporating the
knowledge of the business domain experts at
run time according to the changes in the
environment where the context model will be
5) Relevance to environment (RV): this criterion
measures the relevance of the contextual model
to both the environment in which it is sensed and
the environment in which it will be used to
support context aware decision making
Table 1: Modeling techniques comparison.
column 1
Model for
The relevance to environment (RV), adaptability
to change (AC) and ease of use (EU) are the main
edges of the solution methodology proposed in this
In this research work we propose a solution that
senses and identifies different types of business
contextual elements. The solution models the
contextual elements related to different business
domains by building a library of aspects for each
business domain inside one of the existing context
awareness frameworks. The output of the extended
Context awareness framework is a set of apsectized
contextual elements related to business processes for
a specific industry. The aspectized contextual facts
can be formulated in any mark-up language (e.g.
XML) and fed into any business process modeler to
model the business process and its embedded
decision-maker according to a simple intelligence
tree defined by business domain experts. Our
methodology of aspectized context-awareness for
business processes could be summarized in the
following steps and sub steps:
4.1 Context Sensation and
As our main focus is on contextual aspects related to
a business process, the main aspects that we take
into consideration are non-human resource
utilization, human resource utilization, human
resource experience level, organizational strategies,
risk factors associated with a process, industry
regulations and practices affecting a process, timing
and season of process execution. Context sensation
happens by utilizing sensors and context entities of
an existing context awareness framework which is
the Java context Awareness Framework (JCAF),
designed initially for pervasive systems. JCAF has
several edges which made it the most convenient
tool to extend on and to test our new methodology:
1) JCAF is an extensible Open Source tool
2) It supports the extraction of context information
from the different types of context sensors
(physical, virtual and logical context sensors)
3) It allows the addition of new libraries of aspects
which makes it possible to model contextual
concerns as aspects/cross cutting concerns
related to the business process entity
4) It provides easy ways to add classes
representing different types of entities
5) It takes the quality of context (QoC) aspect into
consideration. It has a get_Accuracy and Secure
methods within the JCAF Context Item class
and these methods can be overridden to specify
the combination of quality guarantees for the
context items (Bardram, 2005)
We added a library of aspects to the JCAF
framework, where all the types of cross cutting
concerns are defined as well as the weaving method.
The open aspects approach is utilized in this library
to allow proper combination of change events and
corrective actions. Thus the extended framework
serves in producing aspectized contextual entities
representing the state of the context of the targeted
business process.
4.2 Aspectized Context Classification
After appropriately extracting and sensing
contextual information, the contextual data is
classified into the four contextual layers defined by
Rosemann (2008, pp.3-4): Immediate, Internal,
External and Environmental.
The importance of context classification lies in
the fact that the layer to which a contextual variable,
or its constituent elements belong, defines the level
of impact of this contextual variable or element on
the business. In more specific terms, each contextual
layer would have a specific set of goals (whether
high level business goals or operational goals) that it
impacts (i.e. the contextual variables or elements
that belong to this contextual layer and would also
impact the high level goals and operational goals
that this contextual layer impacts). The goals that are
impacted by each of the four contextual layers
defined by Rosemann (2008, pp.3-4) would differ
for each industry considered within the scope of our
Through these important links between the
contextual variables and constituent elements and
goals we are able to identify which contextual
variables affect which business process. As we link
the goals of the business process with the goals of
the contextual variables and detect the common
goals, we identify which contextual variables and
elements affect which business processes and which
business process steps to take.
The contextual variables/elements classification
cannot be automatically deduced as it would differ
from one industry to another and various industry
experts may have their different views about them
(e.g. weather could be an immediate context item in
one industry while in another industry it could be an
environmental context item). As a result, the most
appropriate approach for classification is to allow
the industry/business process experts to define their
own classification in an easily updatable way. Thus
we can have two repositories, a repository for each
PECCS 2012 - International Conference on Pervasive and Embedded Computing and Communication Systems
industry/ business domain (where the business
domain experts define in any near natural language
syntax the industry goals, the most important context
elements related to the industry, the business
processes under this industry) and another business
process repository defined by business process
experts (having information related to the business
process steps and alternatives, the business process
specific goals as well as possible recommendations
for business process flow ).
4.3 Context Variables and Business
Processes Matching
The goal of this step is identifying which aspectized
contextual variables/ elements affect which business
processes and which steps to take within these
processes. This can be achieved by identifying the
goals of the business process under investigation. It
comes by studying the business behind the process
and the wider picture that the business process fits
in, which comes from the understanding of the
overall business domain. As mentioned above, the
goals of the industry as well as the business process
goals should be defined by business domain and
process experts in an easily updatable format. This is
followed by comparing the goals of the business
process to the goals of the different aspects of
contextual elements that are of interest to the
industry under which the business process lies and
detecting any common goals. If common goals are
found then the business process is affected by the
context and through common goals we will be able
to identify which business process steps are affected.
4.4 Business Process Configuration
Configuring the affected business process according
to the values of the contextual variables takes place
as depicted in figure 1. After defining which
business processes and which sub processes or steps
are affected by which contextual variables and
elements, the important issue now is the
recommendations about possible configurations. In
fact this could be done in two ways:
a. Within our custom developed framework
without integrating or extending any
business process modeling software: by
having a recommendations engine which has
ranges for different contextual variable/elements
and for each range it gives recommendations for
the steps of the business process. This method
requires an easy way for industry experts to
define recommendations. This could be
achieved by having recommendations
definitions inside the business processes
repository which would have ranges for
different contextual elements and according to
these ranges, recommendations for alternative
flows of the business process are made. In this
case a decision maker class inside the
framework compares the goals and defines
which processes and steps are affected by which
variables then reads the recommendations from
the recommendation files and publishes them
b. Using an external business process modeling
framework: this could take recommendations
in a specific format and make use of the
recommendations in addition to the modeler’s
capabilities, to make the right decision
regarding the business process flow.
Figure 1: Business process configuration steps.
4.5 Extensibility of the Solution
The main source of the extensibility is finding an
easy way for industry/business process experts to
update information related to the business goals of
the industry, its context variables, their classification
as well as the different business processes and
alternatives within the industry along with their
associated goals.
The business experts can easily use the
framework for defining new industries and for
defining their business goals, contextual layers and
contextual variables and their associated list of
business processes. For each business process they
can also define the business process and the
recommendations according to contextual variables’
threshold values that are defined by business process
experts and advices to actions or best mitigation
within each range of thresholds of contextual
variables values.
Figure 2 presents an example of the airlines check in
business process configuration steps which could
take place using the above explained methodology.
Figure 2: Check in- business process configuration.
In the above example the JCAF senses different
contextual variables related to the airlines industry
and represents them as open aspects. Classification
of the contextual aspects takes place in the four
contextual layers (immediate, internal, external, and
environmental) defined earlier. According to this
classification goals matching is done using
additional goal matching classes added to JCAF and
we discover that the season and number of check in
counters aspects affects step 1(Ticket Category
Validation) and step 3 (Passenger Seating Choice) of
the Check In Business Process. The values of these
two aspects are computed and recommendations for
the ranges of values of these aspects are fetched
from the business process repository (defined by the
business process experts). The framework
recommends skipping step 1 (thus availing all
counters to everyone), skipping step 3 and making
passengers seating automatic to speed up the process
and avoid bottlenecks which resulted from the
current contextual situation.
In this paper we present an aspect-oriented
methodology for representing business process
context to support informed business process
decision making. The context is modeled in terms of
Open Aspects and a goal driven approach is used to
classify the contextual aspects and determine their
impact on different business processes and
operational levels. Recommendations about the
business process flow are formulated based on
aspectized contextual facts. We have so far
implemented the first part of the framework which
involves the extension of JCAF with the aspects
library and the representation of sensed contextual
items as aspects and converting them to XML
format. This is in addition to the classification of
contextual items and the relationships between the
items and business processes through goals. Our
next step is to combine the generated XML files
with the IBM Web sphere business modeler tool to
observe how the recommendations and contextual
findings would affect the business process decisions.
We express our thanks to Dr. Jacob Bardram and
Mr. Senzo Karolly for supporting our use of JCAF.
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