Mining Expressive and Executable Resource-Aware Imperative Process Models View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-05-16

AUTHORS

Cristina Cabanillas , Stefan Schönig , Christian Sturm , Jan Mendling

ABSTRACT

Process mining extracts relevant information on executed business processes from historical data stored in event logs. The data typically available include the activities executed, temporal information and the resources in charge of their execution. With such data, the functional, behavioural and organisational perspectives of a process can be discovered. Many existing process mining approaches are capable of generating representations involving the first two perspectives with all types of processes. The extraction of simple and complex resource assignment rules has also been tackled with declarative process models. However, it is noticeable that despite imperative notations like BPMN are mostly used for process modelling nowadays, the existing process mining approaches for enriching such models with resource assignments cannot discover rules like separation of duties and do not produce executable resource-aware process models. In this paper we present an approach for mining resource-aware imperative process models that uses an expressive resource assignment language (RALph) with the de-facto standard notation BPMN. The organisational perspective of the resulting models can be automatically analysed thanks to the formal semantics of RALph. The method has been implemented and tested with a real use case. More... »

PAGES

3-18

References to SciGraph publications

  • 2017. Discovering Causal Factors Explaining Business Process Performance Variation in ADVANCED INFORMATION SYSTEMS ENGINEERING
  • 2013. Enhancing Declare Maps Based on Event Correlations in BUSINESS PROCESS MANAGEMENT
  • 2009-05. Declarative workflows: Balancing between flexibility and support in COMPUTER SCIENCE - RESEARCH AND DEVELOPMENT
  • 2003-02. Vacuity detection in temporal model checking in INTERNATIONAL JOURNAL ON SOFTWARE TOOLS FOR TECHNOLOGY TRANSFER
  • 2005. An Efficient Implementation of Sugiyama’s Algorithm for Layered Graph Drawing in GRAPH DRAWING
  • 2010. Analyzing Resource Behavior Using Process Mining in BUSINESS PROCESS MANAGEMENT WORKSHOPS
  • 2013. Fundamentals of Business Process Management in NONE
  • 2016. Efficient and Customisable Declarative Process Mining with SQL in ADVANCED INFORMATION SYSTEMS ENGINEERING
  • 2005. Workflow Resource Patterns: Identification, Representation and Tool Support in ACTIVE FLOW AND COMBUSTION CONTROL 2018
  • 2015. RALph: A Graphical Notation for Resource Assignments in Business Processes in ADVANCED INFORMATION SYSTEMS ENGINEERING
  • 2011. XES, XESame, and ProM 6 in PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS
  • 2014. Process Mining from the Organizational Perspective in FOUNDATIONS OF INTELLIGENT SYSTEMS
  • Book

    TITLE

    Enterprise, Business-Process and Information Systems Modeling

    ISBN

    978-3-319-91703-0
    978-3-319-91704-7

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-91704-7_1

    DOI

    http://dx.doi.org/10.1007/978-3-319-91704-7_1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1103994499


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