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Ein Business Process Model Repository für die Automatisierung von mehrstufigen Geschäftsprozessen mit Multilevel Business Artifacts

Translated title of the contribution: A Business Process Model Repository for Automating Multi-Level Business Processes with Multilevel Business Artifacts
  • Michael Weichselbaumer

Research output: ThesisMaster's / Diploma thesis

Abstract

Organizations are often structured hierarchically. Accordingly, the activities of such organizations are distributed over different hierarchical levels. The lack of support for mapping hierarchies in common modeling languages designed for process models often results in incomplete or incomprehensible models. Multilevel modeling extends the existing paradigm in the field of modeling and aims to improve the usability of models. This is to be achieved through reduced complexity and improved extensibility when compared to conventional modeling approaches. Multilevel Business Artifacts enable the use of these advantages by combining data and process models for multiple hierarchical levels of an organization in a single object. This thesis describes the implementation of a repository that allows the management of Multilevel Business Artifacts in hetero-homogeneous concretization hierarchies. Additionally, the repository allows step-by-step refinements of Multilevel Business Artifacts by providing a set of reflective functions that adhere to freely definable consistency criteria.
Translated title of the contributionA Business Process Model Repository for Automating Multi-Level Business Processes with Multilevel Business Artifacts
Original languageGerman (Austria)
Supervisors/Reviewers
  • Schrefl, Michael, Supervisor
  • Schütz, Christoph Georg, Co-supervisor
Publication statusPublished - Apr 2020

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102035 Data science
  • 502050 Business informatics
  • 503008 E-learning

JKU Focus areas

  • Digital Transformation

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