A Unified Conceptual Model Based on Business Artifacts for Information Systems

Maroun Abi Assaf, Charbel Fares, Ali Rachini, Youakim Badr, Kablan Barbar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Conceptual modeling captures Information Systems requirements and specifications in a graphical representation at a high-level without including low-level implementation details. Entity Relationship Model (ER Model) and Business Process Model and Notation (BPMN) are two major conceptual models for modeling respectively data and process aspects of an Information System. On the other hand, Conceptual Artifact Model (CAM) is an alternative conceptual model for modeling both data and process aspects in a single model based on the notion of Artifacts. In this article, we formalize the CAM and define algorithms for generating both Database and Workflow specifications from this model. These specifications are then used to create the Relational Database and execute the Workflow of the Information System. Benefits of such alternative modeling approach are not limited to reducing the time and effort of designing Information Systems but also of implementing them.

Original languageEnglish (US)
Title of host publication2023 24th International Arab Conference on Information Technology, ACIT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350384307
DOIs
StatePublished - 2023
Event24th International Arab Conference on Information Technology, ACIT 2023 - Ajman, United Arab Emirates
Duration: Dec 6 2023Dec 8 2023

Publication series

Name2023 24th International Arab Conference on Information Technology, ACIT 2023

Conference

Conference24th International Arab Conference on Information Technology, ACIT 2023
Country/TerritoryUnited Arab Emirates
CityAjman
Period12/6/2312/8/23

All Science Journal Classification (ASJC) codes

  • Marketing
  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Information Systems
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Modeling and Simulation

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