Stijn Goedertier

Designing compliant business processes with obligations and permissions

The sequence and timing constraints on the activities in business processes are an important aspect of business process compliance. To date, these constraints are most often implicitly transcribed into control-flow-based process models. This implicit representation of constraints, however, complicates the verification, validation and reuse in business process design. In this paper, we investigate the use of temporal deontic assignments on activities as a means to declaratively capture the control-flow semantics that reside in business regulations and business policies. In particular, we introduce PENELOPE, a language to express temporal rules about the obligations and permissions in a business interaction, and an algorithm to generate compliant sequence-flow-based process models that can be used in business process design.

Process discovery in event logs: An application in the telecom industry

The abundant availability of data is typical for information-intensive organizations. Usually, discerning knowledge from vast amounts of data is a challenge. Similarly, discovering business process models from information system event logs is definitely non-trivial. Within the analysis of event logs, process discovery, which can be defined as the automated construction of structured process models from such event logs, is an important learning task. However, the discovery of these processes poses many challenges. First of all, human-centric processes are likely to contain a lot of noise as people deviate from standard procedures. Other challenges are the discovery of so-called non-local, non-free choice constructs, duplicate activities, incomplete event logs and the inclusion of prior knowledge. In this paper, we present an empirical evaluation of three state-of-the-art process discovery techniques: Genetic Miner, AGNEs and HeuristicsMiner. Although the detailed empirical evaluation is the main contribution of this paper to the literature, an in-depth discussion of a number of different evaluation metrics for process discovery techniques and a thorough discussion of the validity issue are key contributions as well.

Declarative process modeling with business vocabulary and business rules

A process modeling language is declarative when it explicitly takes into account the business concerns that govern business processes. In this paper, we show how business concerns can be modeled declaratively using a fact-oriented business vocabulary that allows to express sixteen different business rule types. In particular, we present the EMBrA 2CE Framework, an extension of the SBVR that allows for declarative process modeling.

Specifying process-aware access control rules in SBVR

Access control is an important aspect of regulatory compliance. Therefore, access control specifications must be process-aware in that they can refer to an underlying business process context, but do not specify when and how they must be enforced. Such access control specifications are often expressed in terms of general rules and exceptions, akin to defeasible logic. In this paper we demonstrate how a role-based, process-aware access control policy can be specified in the SBVR. In particular, we define an SBVR vocabulary that allows for a process-aware specification of defeasible access control rules. Because SBVR does not support defeasible rules, we show how a set of defeasible access control rules can be transformed into ordinary SBVR access control rules using decision tables as a transformation mechanism.

Declarative business process modelling: principles and modelling languages

The business process literature has proposed a multitude of business process modelling approaches or paradigms, each in response to a different business process type with a unique set of requirements. Two polar paradigms, i.e. the imperative and the declarative paradigm, appear to define the extreme positions on the paradigm spectrum. While imperative approaches focus on explicitly defining how an organisational goal should be reached, the declarative approaches focus on the directives, policies and regulations restricting the potential ways to achieve the organisational goal. In between, a variety of hybrid-paradigms can be distinguished, e.g. the advanced and adaptive case management. This article focuses on the less-exposed declarative approach on process modelling. An outline of the declarative process modelling and the modelling approaches is presented, followed by an overview of the observed declarative process modelling principles and an evaluation of the declarative process modelling approaches.

Process mining as first-order classification learning on logs with negative events

Process mining is the automated construction of process models from information system event logs. In this paper we identify three fundamental difficulties related to process mining: the lack of negative information, the presence of history-dependent behavior and the presence of noise. These difficulties can elegantly dealt with when process mining is represented as first-order classification learning on event logs supplemented with negative events. A first set of process discovery experiments indicates the feasibility of this learning technique.

Rule-based business process modelling and enactment

A business process model is called rule-based if the logic of its control flow, data flow and resource allocation is declaratively expressed by means of business rules. Business rules are recognised as powerful representation forms that can potentially define the semantics of business process models and business vocabulary. To date, however, there is little consensus and fragmentary knowledge about the precise relationship between these elements of business modelling. In this article, we develop a first-version metamodel that is to be used as a foundation in integrating and developing existing and new forms of rule-based business process modelling. In addition, we show how rule-based process models can be brought to execution in the context of service-oriented architecture.

A New Approach for Discovering Business Process Models from Event Logs

Process mining is the automated acquisition of process models from the event logs of information systems. Although process mining has many useful applications, not all inherent difficulties have been sufficiently solved. A first difficulty is that process mining is often limited to a setting of non-supervised learnings since negative information is often not available. Moreover, state transitions in processes are often dependent on the traversed path, which limits the appropriateness of search techniques based on local information in the event log. Another difficulty is that case data and resource properties that can also influence state transitions are time-varying properties, such that they cannot be considered ascross-sectional.This article investigates the use of first-order, ILP classification learners for process mining and describes techniques for dealing with each of the above mentioned difficulties. To make process mining a supervised learning task, we propose to include negative events in the event log. When event logs contain no negative information, a technique is described to add artificial negative examples to a process log. To capture history-dependent behavior the article proposes to take advantage of the multi-relational nature of ILP classification learners. Multi-relational process mining allows to search for patterns among multiple event rows in the event log, effectively basing its search on global information. To deal with time-varying case data and resource properties, a closed-world version of the Event Calculus has to be added as background knowledge, transforming the event log effectively in a temporal database. First experiments on synthetic event logs show that first-order classification learners are capable of predicting the behavior with high accuracy, even under conditions of noise.

A vocabulary and execution model for declarative service orchestration

In this paper we introduce the EM-BrA2CE Framework: a vocabulary and execution model for dynamic service orchestration that allows to combine many business rule types, independently of the used methods for knowledge representation and reasoning. The vocabulary is described in terms of the Semantics for Business Vocabulary and Rules (SBVR) and the execution model is presented as a colored Petri net (CP-Net).

A phased deployment of a workflow infrastructure in the enterprise architecture

Many organizations migrate to service-oriented architecture (SOA) since it caters for the demanded flexibility and reusability in information systems. Besides delineating appropriate business services, a mechanism for coordinating these services is needed to support business processes. The current state-of-the-art falls short in realizing that goal since existing standards and software packages tend to neglect existing enterprise architectures. Moreover they assume a central position in the architecture from which they control all services according to prescriptive process models, which makes them rather useless in a realistic setting. Therefore we introduce four dimensions to classify workflow engines that reflect the degree of support for the presented requirements. Subsequently we combine these dimensions to describe a phased roll-out of a solution that fulfills the requirements. That solution is currently deployed at KBC Bank & Insurance Group.