Automatic Generation of a Data-Centered View of Business Processes Cristina Cabanillas1, Manuel Resinas1, Antonio Ruiz-Cort�� es1, and Ahmed Awad2 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. H. Mouratidis and C. Rolland (Eds.): CAiSE 2011, LNCS 6741, pp. 352���366, 2011. c Springer-Verlag Berlin Heidelberg 2011

Automatic Generation of a Data-Centered View of Business Processes 353 commonly used BP models and notations focus on the control flow and the tim- ing of activities in the BP. As a consequence, in most BP models, data (e.g., documents, reports, invoices, emails and the like) play a secondary role, just as inputs or outputs of the activities of the process. Nevertheless, understanding and analysing how data is modified during the ex- ecution of a BP is getting an increased interest from both industry and academy. For instance, BPMN, the de-facto standard for BP modelling, has incorporated more advanced constructs for data management in its last version [1]. In addi- tion, there is an increasing number of research proposals to analyse the way data is used in a BP to detect anomalies [2,3,4] and to define data-aware compliance rules [5] for BPs. Therefore, providing a mechanism to transform from the usual activity-centered view of a BP to a data-centered view that focuses on the data handled during the process is very appealing to this goal of understanding and analysing how data is modified during the execution of a BP. In this paper we describe a model-driven procedure based on Petri nets for carrying out this transformation automatically. In particular, the input of the procedure is a BP diagram expressed in BPMN 2.0 (cf. Figure 1). We use this notation because it is the de-facto standard for BP modelling. Such diagrams represent data objects connected to the BP activities that use them either to read them or write them, or for both things. A data object has a type and can have one or more states along the execution of a process. For instance, in the BP of opening a bank account, the data object application filled by the new customer could go through states sent, accepted and stored. The output of the procedure is a data-centered view composed of the set of object life cycles (OLCs) of all the data objects that are involved in a BP. They represent the allowed transitions between the states of the data object according to the BP diagram. In addition, these transitions also include information about the activities of the BP that are executed in the transition between states of the data object (cf. Figure 2). Furthermore our procedure also deals with some data anomalies that may appear in a BP model (cf. Section 4 for more details). Our approach has the following advantages: (i) it is fully automated (ii) it is based on Petri nets, which allows us to use e���cient and well-tested Petri net algorithms (iii) since it includes information about the activities that are executed in each transition, it provides the same full information required to understand BP execution as activity-centered process diagrams and (iv) it is robust in the sense that it provides an accurate data-centered view despite having a BP with data anomalies as input. Moreover, it informs the user about these data anomalies. The remaining of the paper is organised as follows. Section 2 introduces a use case used to exemplify the output produced by the procedure. Section 3 contains the description of the whole procedure for OLC generation. In Section 4 the detection and handling of data anomalies is introduced. Section 5 contains a summary of related work and in Section 6 we draw a set of conclusions and outline some future work.

354 C. Cabanillas et al. INTERNATIONAL OLYMPIC COMMITTEE INTERNATIONAL OLYMPIC COMMITTEE Collect candidates Assess candidates Approve accepted candidates Vote Check winner Delete last position Is there a winner? Notify results Publish winner Candidatures created Candidatures assessed Candidatures selected Resolution created Candidatures updated Resolution updated Resolution notified Resolution published Candidatures stored No Yes Fig. 1. Business process for assigning the venue for the Olympic Games 2 Use Case To illustrate our approach we use the BP for assigning the venue for the Olympic Games (Figure 1) as use case in this paper1. The International Olympic Com- mittee is in charge of this process. This committee first receives the applications of the cities that want to organize the Olympic Games. Each city is evaluated in order to keep only those which fulfill all the requirements. After this filter is ap- plied, an approval of the final candidates is necessary. Once the list of candidates is ready, a secret voting is carried out. If there is consensus and only one city is selected, then the winner venue is published. Otherwise, the least voted city is eliminated from the list of candidates and a new voting is performed. This is repeated until there are only two cities left. Then, the city with a greatest number of votes wins. There are two data objects in this BP model. Data object Candidates repre- sents a document that contains a list of the cities that applied for the venue. The information of each candidate in the document includes the name of the city, its description, what it offers for each requirement needed, and the mark given by the committee to discern between accepted and rejected candidates. This document may be updated during the voting repetitive process. Data object Resolution represents the result of the voting and, thus, is a document with the same list of candidates and the number of votes each of them received. Again, this data object will be updated if more than one voting is performed. If there is no winner yet, the resolution is notified. Otherwise, the resolution is completed with the features of the final venue and published. The output of the procedure presented in this paper is a set of finite-state machines (FSM) representing the life cycles of the data objects modelled in a 1 Note that this process is used for illustration purposes only, so there may be differ- ences with the actual process of the Olympic Games venue selection process.