Conformance checking and diagnosis for declarative business process models in data-aware scenarios

Borrego, Diana; Barba, Irene

doi:10.1016/j.eswa.2014.03.010

Cited by 44 publications

(34 citation statements)

References 26 publications

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“…Furthermore, (Jiménez-Ramírez & Barba, 2013) proposed a basic resource perspective for Declare called ConDec-R. And finally, for the data perspective multiple extensions have been proposed. (Borrego & Barba, 2014;Montali et al, 2013) both propose extensions (Declare ++ and unnamed) for Declare to add simple decision logic to Declare constraints (e.g., one data value).…”

Section: Related Workmentioning

confidence: 99%

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Mertens

Gailly

Poels

2017

Expert Systems with Applications

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Abstract. Modeling loosely framed and knowledge-intensive business processes with the currently available process modeling languages is very challenging. Some lack the flexibility to model this type of processes, while others are missing one or more perspectives needed to add the necessary level of detail to the models. In this paper we have composed a list of requirements that a modeling language should fulfil in order to adequately support the modeling of this type of processes. Based on these requirements, a metamodel for a new modeling language was developed that satisfies them all. The new language, called DeciClare, incorporates parts of several existing modeling languages, integrating them with new solutions to requirements thathad not yet been met. Deciclare is a declarative modeling language at its core, and therefore, can inherently deal with the flexibility required to model loosely framed processes. The complementary resource and data perspectives add the capability to reason about, respectively, resources and data values. The latter makes it possible to encapsulate the knowledge that governs the process flow by offering support for decision modeling. The abstract syntax of DeciClare has been implemented in the form of an Ecore model. Based on this implementation, the language-domain appropriateness of the language was validated by domain experts using the arm fracture case as application scenario.

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Section: Related Workmentioning

confidence: 99%

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Mertens

Gailly

Poels

2017

Expert Systems with Applications

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“…In a recent work, reported in [20], the data perspective for conformance checking with Declare is expressed in terms of conditions on global variables disconnected from the specific Declare constraints expressing the control flow. This work does not take the temporal perspective into account.…”

Section: Related Workmentioning

confidence: 99%

“…[16,17,18]). More recently the additional data perspective has been considered in [19,20], even if in these works the data perspective is not fully integrated with the control flow perspective. Efficient and fully integrated multi-perspective conformance checking proposals for declarative models, however, are still missing.…”

Section: Introductionmentioning

confidence: 99%

Conformance checking based on multi-perspective declarative process models

Burattin

Maggi

Sperduti

2016

Expert Systems with Applications

139

112

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Process mining is a family of techniques that aim at analyzing business process execution data recorded in event logs. Conformance checking is a branch of this discipline embracing approaches for verifying whether the behavior of a process, as recorded in a log, is in line with some expected behaviors provided in the form of a process model. The majority of these approaches require the input process model to be procedural (e.g., a Petri net). However, in turbulent environments, characterized by high variability, the process behavior is less stable and predictable. In these environments, procedural process models are less suitable to describe a business process. Declarative specifications, working in an open world assumption, allow the modeler to express several possible execution paths as a compact set of constraints. Any process execution that does not contradict these constraints is allowed. One of the open challenges in the context of conformance checking with declarative models is the capability of supporting multi-perspective specifications. In this paper, we close this gap by providing a framework for conformance checking based on MP-Declare, a multi-perspective version of the declarative process modeling language Declare. The approach has been implemented in the process mining tool ProM and has been experimented in three real life case studies.

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“…This is achieved by adding support to Declare to model decision logic, without losing sight of the need for flexibility of KiPs. Making the decision logic explicit also facilitates the justification of taken decisions, better conformance checking and reuse [18] across different processes or even organizations. Value is created for the users and the organization as declarative process modeling languages are better suited for these types of processes compared to traditional process modeling languages.…”

Section: Analysis Of the Declare-r-dmn Languagementioning

confidence: 99%

Enhancing Declarative Process Models with DMN Decision Logic

Mertens

Gailly

Poels

2015

Enterprise, Business-Process and Information Systems Modeling

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Abstract. Modeling dynamic, human-centric, non-standardized and knowledgeintensive business processes with imperative process modeling approaches is very challenging. Declarative process modeling approaches are more appropriate for these processes, as they offer the run-time flexibility typically required in these cases. However, by means of a realistic healthcare process that falls in the aforementioned category, we demonstrate in this paper that current declarative approaches do not incorporate all the details needed. More specifically, they lack a way to model decision logic, which is important when attempting to fully capture these processes. We propose a new declarative language, Declare-R-DMN, which combines the declarative process modeling language Declare-R with the newly adopted OMG standard Decision Model and Notation. Aside from supporting the functionality of both languages, Declare-R-DMN also creates bridges between them. We will show that using this language results in process models that encapsulate much more knowledge, while still offering the same flexibility.

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Conformance checking and diagnosis for declarative business process models in data-aware scenarios

Cited by 44 publications

References 26 publications

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Conformance checking based on multi-perspective declarative process models

Enhancing Declarative Process Models with DMN Decision Logic

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