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Process Querying Methods

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This book presents a framework for developing as well as a comprehensive collection of state-of-the-art process querying methods. Process querying combines concepts from Big Data and Process Modeling and Analysis with Business Process Intelligence and Process Analytics to study techniques for retrieving and manipulating models of real-world and envisioned processes to organize and extract process-related information for subsequent systematic use.

The book comprises sixteen contributed chapters distributed over four parts and two auxiliary chapters. The auxiliary chapters by the editor provide an introduction to the area of process querying and a summary of the presented methods, techniques, and applications for process querying. The introductory chapter also examines a process querying framework. The contributed chapters present various process querying methods, including discussions on how they instantiate the framework components, thus supporting the comparison of the methods. The four parts are due to the distinctive features of the methods they include. The first three are devoted to querying event logs generated by IT-systems that support business processes at organizations, querying process designs captured in process models, and methods that address querying both event logs and process models. The methods in these three parts usually define a language for specifying process queries. The fourth part discusses methods that operate over inputs other than event logs and process models, e.g., streams of process events, or do not develop dedicated languages for specifying queries, e.g., methods for assessing process model similarity.

This book is mainly intended for researchers. All the chapters in this book are contributed by active researchers in the research disciplines of business process management, process mining, and process querying. They describe state-of-the-art methods for process querying, discuss use cases of process querying, and suggest directions for future work for advancing the field. Yet, also other groups like business or data scientists and other professionals, lecturers, graduate students, and tool vendors will find relevant information for their distinctive needs.

Chapter "Celonis PQL: A Query Language for Process Mining" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Inhaltsverzeichnis

Frontmatter
Introduction to Process Querying
Abstract
This chapter gives a brief introduction to the research area of process querying. Concretely, it articulates the motivation and aim of process querying, gives a definition of process querying, presents the core artifacts studied in process querying, and discusses a framework for guiding the design, implementation, and evaluation of methods for process querying.
Artem Polyvyanyy

Event Log Querying

Frontmatter
BP-SPARQL: A Query Language for Summarizing and Analyzing Big Process Data
Abstract
In modern enterprises, business processes (BPs) are realized over a mix of workflows, IT systems, Web services, and direct collaborations of people. Accordingly, process data (i.e., BP execution data such as logs containing events, interaction messages, and other process artifacts) are scattered across several systems and data sources and increasingly show all typical properties of the Big Data. Understanding the execution of process data is challenging as key business insights remain hidden in the interactions among process entities: most objects are interconnected, forming complex heterogeneous but often semi-structured networks. In the context of business processes, we consider the Big data problem as a massive number of interconnected data islands from personal, shared, and business data. We present a framework to model process data as graphs, i.e., process graph, and present abstractions to summarize the process graph and to discover concept hierarchies for entities based on both data objects and their interactions in process graphs. We present a language, namely BP-SPARQL, for the explorative querying and understanding of process graphs from various user perspectives. We have implemented a scalable architecture for querying, exploration, and analysis of process graphs. We report on experiments performed on both synthetic and real-world datasets that show the viability and efficiency of the approach.
Amin Beheshti, Boualem Benatallah, Hamid Reza Motahari-Nezhad, Samira Ghodratnama, Farhad Amouzgar
Data-Aware Process Oriented Query Language
Abstract
The size of execution data available for process mining analysis grows several orders of magnitude every couple of years. Extracting and selecting the relevant data to enable process mining remains a challenging and time-consuming task. In fact, it is the biggest handicap when applying process mining and other forms of process-centric analysis. This work presents a new query language, DAPOQ-Lang, which overcomes some of the limitations identified in the field of process querying and fits within the Process Querying Framework. The language is based on the OpenSLEX meta model, which combines both data and process perspectives. It provides simple constructs to intuitively formulate questions. The syntax and semantics have been formalized and an implementation of the language is provided, along with examples of queries to be applied to different aspects of the process analysis.
Eduardo Gonzalez Lopez de Murillas, Hajo A. Reijers, Wil M. P. van der Aalst
Process Instance Query Language and the Process Querying Framework
Abstract
The use of Business Process Management Systems (BPMSs) allows companies to manage the data that flows through process models (business instances) and to monitor all the information and actions concerning a process execution. In general, the retrieval of this information is used not only to measure whether the process works as expected but also to enable assistance in future process improvements by means of a postmortem analysis. This chapter shows how the measures extracted from the process instances can be employed to adapt business process executions according to other instances or other processes, thereby facilitating the adjustment of the process behavior at run-time to the organization needs. A language, named Process Instance Query Language (PIQL), is introduced. This language allows business users to query the process instance measures at run-time. These measures may be used both inside and outside the business processes. As a consequence, PIQL might be used in various scenarios, such as in the enrichment of the information used in Decision Model and Notation tables, in the determination of the most suitable business process to execute at run-time, and in the query of the instance measures from a dashboard. Finally, an example is introduced to demonstrate PIQL.
Jose Miguel Pérez Álvarez, Antonio Cancela Díaz, Luisa Parody, Antonia M. Reina Quintero, María Teresa Gómez-López

Process Model Querying

Frontmatter
The Diagramed Model Query Language 2.0: Design, Implementation, and Evaluation
Abstract
The Diagramed Model Query Language (DMQL) is a structural query language that operates on process models and related kinds of models, e.g., data models. In this chapter, we explain how DMQL works and report on DMQL’s research process, which includes intermediate developments. The idea of a new model query language came from observations in industry projects, where it was necessary to deal with a variety of modeling languages, complex query requirements, and the need for pinpointing the query results. Thus, we developed the Generic Model Query Language (GMQL) tailored to deal with models of arbitrary modeling languages and queries that express model graph structures of any complexity. GMQL queries are formulas and professionals expressed the need to specify queries more conveniently. Therefore, the next development step was DMQL, which comes with functionality similar to GMQL, but allows to specify queries graphically. In this chapter, we describe both query languages, their syntax, semantics, implementation, and evaluation and come up with a new version of DMQL, which includes new functionality. Finally, we relate GMQL and DMQL to the Process Querying Framework.
Patrick Delfmann, Dennis M. Riehle, Steffen Höhenberger, Carl Corea, Christoph Drodt
VM*: A Family of Visual Model Manipulation Languages
Abstract
Context: Practical facilities for querying, constraining, and transforming models (“model management”) can significantly improve the utility of models, and modeling. Many approaches to model management, however, are very restricted, thus diminishing their utility: they support only few use cases, model types or languages, or burden users to learn complex concepts, notations, and tools.
Goal: We envision model management as a commodity, available with little effort to every modeler, and applicable to a wide range of use cases, modeling environments, and notations. We aim to achieve this by reusing the notation for modeling as a notation for expressing queries, constraints, and transformations.
Method: We present the VM* family of languages for model management. In support of our claim that VM* lives up to our vision we provide as evidence a string of conceptual explorations, prototype implementations, and empirical evaluations carried out over the previous twelve years.
Results: VM* is viable for many modeling languages, use cases, and tools. Experimental comparison of VM* with several other model querying languages has demonstrated that VM* is an improvement in terms of understandability. On the downside, VM* has limits regarding its expressiveness and computational complexity.
Conclusions: We conclude that VM* largely lives up to its claim, although the final proof would require a commercial implementation, and a large-scale industrial application study, both of which are beyond our reach at this point.
Harald Störrle, Vlad Acreţoaie
The BPMN Visual Query Language and Process Querying Framework
Abstract
Business needs often demand business analysts to inspect large and intricate business process models for analysis and maintenance purposes. Nevertheless, manually retrieving information in these complex models is not a rewarding error-free activity. The automatic querying of process models and visualization of the retrieved results represents a useful opportunity for business analysts in order to save their time and effort. This demands for languages that can express process model characteristics and, at the same time, are easy to use for and close enough to the knowledge of people working with process models. This chapter provides an overview of BPMN VQL, one of the languages for querying business processes. BPMN VQL allows business analysts to query process models and retrieve both structural information and knowledge related to the domain. Beyond the performance of the query language implementation, we have investigated the benefits and drawbacks of its use. An empirical study with human subjects has been conducted in order to evaluate the advantages and the effort required, both for BPMN VQL query formulation and understanding.
Chiara Di Francescomarino, Paolo Tonella
Retrieving, Abstracting, and Changing Business Process Models with PQL
Abstract
Due to the increasing adoption of process-aware information systems (PAISs) in enterprises, extensive process model repositories have emerged. In turn, this has raised the need for properly querying, viewing, and evolving process models. In order to enable context-specific views on the latter as well as on related process data, a PAIS should provide sophisticated techniques for abstracting large process models. Moreover, to cope with the complexity of process model changes, domain experts should be supported in evolving process models based on appropriate model abstractions. This chapter presents the PQL language for querying, abstracting, and changing process models. Due to the generic approach taken, the definition of process model abstractions and changes on any graph-based process model notation become possible. Overall, PQL provides a key contribution to take process model repositories to the next level.
Klaus Kammerer, Rüdiger Pryss, Manfred Reichert
QuBPAL: Querying Business Process Knowledge
Abstract
We present a query language, called QuBPAL, for retrieving knowledge from repositories of business processes represented in the BPAL (Business Process Abstract Language) framework. BPAL combines in a single modeling framework the procedural and the ontological aspects of business processes. This is done by providing a uniform, logic-based representation of both the workflow, with its associated procedural semantics, and the domain knowledge that captures the meaning of the entities participating in the process. This uniform representation is achieved by using Logic Programming (LP) as an intermediate language, to which we map BPMN models and OWL/RDF definitions. QuBPAL queries allow combining structural, behavioral, and domain-related knowledge and hence enable reasoning about the process from all these perspectives.
Maurizio Proietti, Francesco Taglino, Fabrizio Smith
CRL and the Design-Time Compliance Management Framework
Abstract
Following the crisis in 2008, the financial industry has faced growing numbers of laws and regulations globally. The number and complexity of these regulations are creating significant issues for governance, risk, and compliance management in almost all industrial sectors. This emergent business need calls for a structured and formal framework for managing business process compliance, which is sustainable throughout the complete business process lifecycle. A preventive focus is essential such that compliance is considered from the early stages of business process design, thus enforcing compliance by design. This chapter introduces the Compliance Request Language (CRL), which is at the heart of a formal design-time compliance verification, analysis, and management framework and addresses the “Check Compliance” use case. Following a model-driven engineering approach, CRL is a graphical domain-specific language that is formally grounded and enables the abstract pattern-based specification of compliance requirements to alleviate the complexities of formal/mathematical languages. An integrated tool-suite has been developed as an instantiation artifact, and the various validation activities have been conducted to ensure the validity, efficacy, and applicability of the proposed language and framework.
Amal Elgammal, Oktay Turetken
Process Query Language
Abstract
A process is a collection of actions that were already, are currently being, or must be taken in order to achieve a goal, where an action is an atomic unit of work, for instance, a business activity or an instruction of a computer program. A process repository is an organized collection of models that describe processes, for example, a business process repository and a software repository. Process repositories without facilities for process querying and process manipulation are like databases without Structured Query Language , that is, collections of elements without effective means for deriving value from them. Process Query Language (PQL) is a domain-specific programming language for managing processes described in models stored in process repositories. PQL can be used to query and manipulate process models based on possibly infinite collections of processes that they represent, including processes that support concurrent execution of actions. This chapter presents PQL, its current features, publicly available implementation, planned design and implementation activities, and open research problems associated with the design of the language.
Artem Polyvyanyy

Event Log and Process Model Querying

Frontmatter
Business Process Query Language
Abstract
Modern Business Process Management systems have to work effectively in a distributed cloud environment and to adapt quickly to dynamic changes. One of the key approaches to increase business process adaptability is to make process definitions more flexible. Usually, this requires to express complex constraints and conditions within a process definition. These complex elements are related to the history of process execution, current organizational and application data. In addition, such complex constraints and conditions should be represented in a standardized and yet simple way. In order to satisfy the above requirements, we need: (1) a business process metamodel that includes proper data structures for process definitions and the history of their execution; (2) a powerful and easy to understand language to query models instantiated from the metamodel; (3) integration of that query language with a widely used business process definition language. In this chapter, we propose Business Process Query Language (BPQL) together with the Business Process Metamodel. BPQL is integrated with the Business Process Model and Notation language increasing significantly its expressiveness and flexibility. We also present results of applying BPQL in the OfficeObjects® WorkFlow system.
Mariusz Momotko, Kazimierz Subieta

Open Access

Celonis PQL: A Query Language for Process Mining
Abstract
Process mining studies data-driven methods to discover, enhance, and monitor business processes by gathering knowledge from event logs recorded by modern IT systems. To gain valuable process insights, it is essential for process mining users to formalize their process questions as executable queries. For this purpose, we present the Celonis Process Query Language (Celonis PQL), which is a domain-specific language tailored toward a special process data model and designed for business users. It translates process-related business questions into queries and executes them on a custom-built query engine. Celonis PQL covers a broad set of more than 150 operators, ranging from process-specific functions to machine learning and mathematical operators. Its syntax is inspired by SQL, but specialized for process-related queries. In addition, we present practical use cases and real-world applications, which demonstrate the expressiveness of the language and how business users can apply it to discover, enhance, and monitor business processes. The maturity and feasibility of Celonis PQL is shown by thousands of users from different industries, who apply it to various process types and huge amounts of event data every day.
Thomas Vogelgesang, Jessica Ambrosy, David Becher, Robert Seilbeck, Jerome Geyer-Klingeberg, Martin Klenk

Other Process Querying Methods

Frontmatter
Process Querying Using Process Model Similarity
Abstract
This chapter describes a specific form of process querying: process querying using process model similarity. This form of process querying can be applied to find one or more process models that are similar to a given query process model. Process querying is useful when searching within a collection of reference process models for a process model that is similar to your own. It is also useful when refactoring a collection of process models, in which case it can be applied to find similar process models and extract the similar parts to create common sub-processes. Process querying consists of a set of measures that can be used to quantify similarity between two process models as well as indexing techniques that can be used to efficiently find a process model within a collection of process models. The chapter shows the applicability of the techniques in a use case.
Remco M. Dijkman, Rik Eshuis
Logic-Based Approaches for Process Querying
Abstract
Today, logic-based formalisms are supported by mature languages, tools, and technologies for querying formal models. In this chapter, we show how process querying can be achieved using these technologies. The main idea is to transform the information of a business process model into a logic-based formalism for which existing query languages can be used. More specifically, we show how Prolog and ontologies together with SPARQL can be used to query BPMN process models.
Ralf Laue, Jorge Roa, Emiliano Reynares, María Laura Caliusco, Pablo Villarreal
Process Model Similarity Techniques for Process Querying
Abstract
Organizations store hundreds or even thousands of models nowadays in business process model repositories. This makes sophisticated operations, like conformance checking or duplicate detection, hard to conduct without automated support. Therefore, querying methods are used to support such tasks. This chapter reports on an evaluation of six techniques for similarity-based search of process models. Five of these approaches are based on Process Model Matching using various aspects of process models for similarity calculation. The sixth approach, however, is based on a technique from Information Retrieval and considers process models as text documents. All the techniques are compared regarding different measures from Information Retrieval. The results show the best performance for the non-matching-based technique, especially when a matching between models is difficult to determine.
Andreas Schoknecht, Tom Thaler, Ralf Laue, Peter Fettke, Andreas Oberweis
Complex Event Processing Methods for Process Querying
Abstract
Business Process Management targets the design, execution, and optimization of business operations. This includes techniques for process querying, i.e., methods to filter and transform business process representations. Some of these representations may assume the form of event data, with an event denoting an execution of an activity as part of a specific instance of a process. In this chapter, we argue that models and methods developed in the general field of Complex Event Processing (CEP) may be exploited for process querying. Specifically, if event data is generated continuously during process execution, CEP techniques may help to filter and transform process-related information by evaluating queries over event streams. Against this background, this chapter first outlines how CEP fits into common use cases and frameworks for process querying. We then review design choices of CEP models that are of importance when adopting the respective techniques. Finally, we discuss techniques for the application of CEP for process querying, namely those for event–process correlation, model-based query generation, automated discovery of event queries, and diagnostics for event query matches.
Han van der Aa, Alexander Artikis, Matthias Weidlich
Process Querying: Methods, Techniques, and Applications
Abstract
Process querying studies concepts and methods from fields like Big data, process modeling and analysis, business process intelligence, and process analytics and applies them to retrieve and manipulate real-world and designed processes. This chapter reviews state-of-the-art methods for process querying, summarizes techniques used to implement process querying methods, discusses typical applications of process querying, and identifies research gaps and suggests directions for future research in process querying.
Artem Polyvyanyy
Backmatter
Metadaten
Titel
Process Querying Methods
herausgegeben von
Dr. Artem Polyvyanyy
Copyright-Jahr
2022
Electronic ISBN
978-3-030-92875-9
Print ISBN
978-3-030-92874-2
DOI
https://doi.org/10.1007/978-3-030-92875-9

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