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Automatic Generation of a Data-Centered View
of Business Processes
Cristina Cabanillas 1 , Manuel Resinas 1 ,
Antonio Ruiz-Cortes 1 ,andAhmedAwad 2
1 Universidad de Sevilla, Spain
{cristinacabanillas,resinas,aruiz}@us.es
2 Hasso Plattner Institute at the University of Potsdam
ahmed.awad@hpi.uni-potsdam.de
Abstract. Most commonly used business process (BP) notations, such
as BPMN, focus on defining the control flow of the activities of a BP,
i.e., they are activity-centered. In these notations, data play a secondary
role, just as inputs or outputs of the activities. However, there is an in-
creasing interest in analysing the life cycle of the data objects that are
handled in a BP because it helps understand how data is modified dur-
ing the execution of the process, detect data anomalies such as checking
whether an activity requires a data object in a state that is unreachable,
and check data compliance rules such as checking whether only a certain
role can change the state of a data object. To carry out such an analy-
sis, it is very appealing to provide a mechanism to transform from the
usual activity-centered model of a BP to the set of life cycles of all the
data objects involved in the process (i.e., a data-centered model). Un-
fortunately, although some proposals describe such transformation, they
do not deal with data anomalies in the original BP model nor include
information about the activities of the BP that are executed in the state
transitions of the data object, which limits the analysis capabilities of
the life cycle models. In this paper, we describe a model-driven proce-
dure to automatically transform from an activity-centered model to a
data-centered model of a BP that solves the aforementioned limitations
of other proposals.
Keywords: business process, data management, object life cycle, data
anomalies, Petri net, reachability graph.
1
Introduction
It is widely known that business processes (BPs) involve different kinds of el-
ements, to be named control flow, time, data and resources. However, most
This work has been partially supported by the European Commission (FEDER),
Spanish Government under the CICYT project SETI (TIN2009-07366); and projects
THEOS (TIC-5906) and ISABEL (P07-TIC-2533) funded by the Andalusian Local
Government.
 
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