Conformance Checking Based on Multi-Perspective Declarative Process Models

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

Aligning Data-Aware Declarative Process Models and Event Logs

Vastavusanalüüs on haru protsessikaevanduses, mis võimaldab analüütikutel saada aru, kas äriprotsesside sooritused järgivad mudeldatud käitumist. Protsesside mudelid võivad olla nii protseduurilised kui ka deklaratiivsed. Kui protseduurilised mudelid kirjeldavad ära täpsed võimalikud tegevused, siis deklaratiivsed mudelid kirjeldavad reeglid, mis peavad olema protsessi sooritusel olema järgitud. Äriprotsesside täitmiste hoiustamiseks kasutatakse sündmuste logisid. Vastavusanalüüsi meetodid kontrollivad erinevaid protsessi sooritusega seotud vaateid, milleks on juhtimisvoog, andmed ja ressursid. Meetodid, mis käsitlevad endas lisaks juhtimisvoole ka andmeid ning ressursse kutsutakse mitmevaatelisteks või andmeteadlikeks lähenemisteks. Mitmevaatelised meetodid annavad rohkem informatsiooni kõrvalekallete kohta võrreldes juhtimisvoogudel põhinevate meetoditega. Joondustel põhinevad vastavusanalüüsi meetodid on olnud edukad nii juhtimisvool põhinevate kui ka andmeteadlike lähenemiste puhul. On olemas mitmeid joondamisel põhinevaid andmeteadlikke lähenemisi protseduuriliste mudelite jaoks, kuid deklaratiivsete mudelite jaoks need puuduvad.Antud töös on kohandatud olemasolev meetod, mis võimaldab sooritada vastavusanalüüsi andmeteadlike protseduuriliste mudelite puhul, kasutades logide joondustel põhinevat meetodit, võimaldamaks kasutamist ka deklaratiivsetel mudelitel. Deklaratiivsetel mudelitel rakendatav meetod implementeeriti moodulina protsessikaeve keskkonna ProM jaoks ja hinnati implementatsiooni kasutades erinevaid sündmuste logisid.Märksõnad: Protsessikaevandus, Deklaratiivsed protsessimudelid, Andmeteadlik vastavusanalüüs, JoondamineConformance checking, a branch of process mining, allows analysts to determine whether the execution of a business process matches the modeled behavior. Process models can be procedural or declarative. Procedural models dictate the exact behavior that is allowed to execute a specific process whilst declarative models implicitly specify allowed behavior with the rules that must be followed during execution. The execution of a business process is represented by event logs. Conformance checking approaches check various perspectives of a process execution including control-flow, data and resources. Approaches that checks not only the control-flow perspective, but also data and resources are called multi-perspective or data-aware approaches. The approaches provide more deviation information than control-flow based techniques. Alignment based techniques of conformance checking have proved to be advantageous in both control-flow based and data-aware approaches. While there exist several data-aware approaches for procedural process models that are based on the principle of finding alignments, there is none so far for declarative process models. In this thesis, we adapt an existing technique for finding alignments of logs and data-aware procedural models to declarative models. We implemented our approach as a plugin of the process mining framework ProM and evaluated it using event logs with different characteristics.Keywords: Process Mining, Declarative Process Models, Data-aware Conformance checking, Alignmen

Rule Mining in Action: The RuM Toolkit

Procedural process modeling languages can be difficult to use for process mining in cases where the process recorded in the event log is unpredictable and has a high number of different branches and exceptions. In these cases, declarative process modeling languages such as DECLARE are more suitable. Declarative languages do not aim at modeling the end-to-end process step by step, but constrain the behavior of the process using rules thus allowing for more variability in the process model yet keeping it compact. Although there are several commercial and academic process mining tools available based on procedural models, there are currently no comparable tools for working with declarative models. In this paper, we present RuM, an accessible and easy-to-use rule mining toolkit integrating multiple DECLARE-based process mining methods into a single unified application. RuM implements process mining techniques based on Multi-Perspective DECLARE, namely the extension of DECLARE supporting data constraints together with controlflow constraints. In particular, RuM includes support for process discovery, conformance checking, log generation and monitoring as well as a model editor. The application has been evaluated by conducting a qualitative user evaluation with eight process analysts

Enhancing BPMN Conformance Checking with OR Gateways and Data Objects

Äriprotsessimudel ja -notatsioon (BPMN) on arenev standard äriprotsesside graafiliseks kujutamiseks. Protsessimudel kirjeldab, kuidas äriprotsess peaks toimima. Kui äriprotsessi tegelikust käitamisest on saadaval ka sündmuste logi, on võimalik vastata küsimusele, kas protsessimudel vastab tegelikkusele. Vastavusanalüüs püüab tuvastada mittevastavusi protsessimudeli ja äriprotsessi käitamisel tekkinud sündmuste logi vahel. BPMN vastavuseanalüsaator on üks Itaalia ettevõtte SIAV-i poolt arendatud protsessikaeve tööriista osadest. Nimetatud tööriistal on aga puudujäägid formaalse semantika osas. Nimelt keskendub vastavusanalüüs järgnevuse voole (control-flow) protsessis, kuid jätab arvesse võtmata andmetevahelisi sõltuvusi. Lisaks ei ole vastavusanalüüsil võimalik kasutada protsessimudeleid, mis sisaldavad OR väravaid (OR gateway). OR-join omab mitme-tähenduslikku semantikat. Se lle konstruktsiooni jaoks on pakutud mitmeid formaalseid semantikaid sarnastes keeltes, nagu EPCs ja YAWL. Nimetatud semantikate kasutatamine mudelite käitamisel ja vastavuse analaüüsil on aga arvutuslikult kulukas. Seega on käesolevas lõputöös implementeeritud OR värava aktiveerimine lineaarse ajalise sõltuvusega mudeli suuruse suhtes. Kuna SIAV-i vastavusanalüsaator ei võta arvesse andmetevahelisi sõltuvusi, võib puudulik analüüs viia vigase vastavusdiagnostikani. Näiteks võib andmeatribuut anda infot selle kohta, et käitati vale tegevus. Kirjeldatud põhjustel ei peaks vastavusanalüsaator tegelema vaid järgnevuse voo vastavuse analüüsiga, vaid peaks arvesse võtma ka andmeid ja nendevahelisi sõltuvusi ning aega. Käesoleva töö teises osas täiendati olemasolevat andmeanalüsaatorit andmeatribuutidega.The Business Process Model and Notation is a developing standard for capturing business processes. Process models describe how the business process is expected to be executed. When a log is available from process executions, this situation raises the interesting question “Are the model and the log conformant?". Conformance checking, also referred to as conformance analysis, aims at the detection of inconsistencies between a process model and its corresponding execution log.The BPMN conformance checker, as a part of a process mining tool, developed an Italian company called SIAV, however, this tool lacks some formal semantics. In particular, the previous conformance checking approach in SIAV tends to focus on the control-flow in a process, while abstracting from data dependencies and process models containing OR gateways could not be used.OR-join has an ambiguous semantics. The several formal semantics of this construct have been proposed for similar languages such as EPCs and YAWL. However, executing and verifying models using these semantics is computationally expensive. Therefore, in this thesis, we implemented enablement of an OR-join in linear time in the size of the workflow graph.Data dependencies are also not considered in conformance checker developed in SIAV, which may lead to misleading conformance diagnostics. For example, a data attribute may provide strong evidence that the wrong activity was executed. That’s why the conformance checker should not only describe the process behaviour from the control flow point of view, but also from other perspectives like data or time. In the second part of the thesis, we enhanced the existing conformance checker with data attributes

Clinical Processes - The Killer Application for Constraint-Based Process Interactions?

For more than a decade, the interest in aligning information systems in a process-oriented way has been increasing. To enable operational support for business processes, the latter are usually specified in an imperative way. The resulting process models, however, tend to be too rigid to meet the flexibility demands of the actors involved. Declarative process modeling languages, in turn, provide a promising alternative in scenarios in which a high level of flexibility is demanded. In the scientific literature, declarative languages have been used for modeling rather simple processes or synthetic examples. However, to the best of our knowledge, they have not been used to model complex, real-world scenarios that comprise constraints going beyond control-flow. In this paper, we propose the use of a declarative language for modeling a sophisticated healthcare process scenario from the real world. The scenario is subject to complex temporal constraints and entails the need for coordinating the constraint-based interactions among the processes related to a patient treatment process. As demonstrated in this work, the selected real process scenario can be suitably modeled through a declarative approach.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

Conformance checking: A state-of-the-art literature review

Conformance checking is a set of process mining functions that compare process instances with a given process model. It identifies deviations between the process instances' actual behaviour ("as-is") and its modelled behaviour ("to-be"). Especially in the context of analyzing compliance in organizations, it is currently gaining momentum -- e.g. for auditors. Researchers have proposed a variety of conformance checking techniques that are geared towards certain process model notations or specific applications such as process model evaluation. This article reviews a set of conformance checking techniques described in 37 scholarly publications. It classifies the techniques along the dimensions "modelling language", "algorithm type", "quality metric", and "perspective" using a concept matrix so that the techniques can be better accessed by practitioners and researchers. The matrix highlights the dimensions where extant research concentrates and where blind spots exist. For instance, process miners use declarative process modelling languages often, but applications in conformance checking are rare. Likewise, process mining can investigate process roles or process metrics such as duration, but conformance checking techniques narrow on analyzing control-flow. Future research may construct techniques that support these neglected approaches to conformance checking

Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

Declarative Guideline Conformance Checking of Clinical Treatments: A Case Study

Conformance checking is a process mining technique that allows verifying the conformance of process instances to a given model. Thus, this technique is predestined to be used in the medical context for the comparison of treatment cases with clinical guidelines. However, medical processes are highly variable, highly dynamic, and complex. This makes the use of imperative conformance checking approaches in the medical domain difficult. Studies show that declarative approaches can better address these characteristics. However, none of the approaches has yet gained practical acceptance. Another challenge are alignments, which usually do not add any value from a medical point of view. For this reason, we investigate in a case study the usability of the HL7 standard Arden Syntax for declarative, rule-based conformance checking and the use of manually modeled alignments. Using the approach, it was possible to check the conformance of treatment cases and create medically meaningful alignments for large parts of a medical guideline

Data-Aware Declarative Process Mining with SAT

Process Mining is a family of techniques for analyzing business process execution data recorded in event logs. Process models can be obtained as output of automated process discovery techniques or can be used as input of techniques for conformance checking or model enhancement. In Declarative Process Mining, process models are represented as sets of temporal constraints (instead of procedural descriptions where all control-flow details are explicitly modeled). An open research direction in Declarative Process Mining is whether multi-perspective specifications can be supported, i.e., specifications that not only describe the process behavior from the control-flow point of view, but also from other perspectives like data or time. In this paper, we address this question by considering SAT (Propositional Satisfiability Problem) as a solving technology for a number of classical problems in Declarative Process Mining, namely log generation, conformance checking and temporal query checking. To do so, we first express each problem as a suitable FO (First-Order) theory whose bounded models represent solutions to the problem, and then find a bounded model of such theory by compilation into SAT