Enterprise Level Integration of Ontology Engineering and Process Mining for Management of Complex Data and Processes to improve Decision System

Tejan Thakar, Tenzin Tsultrim, Larry Stapleton, Liam Doyle

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Software development may involve international-scale, dynamic business processes that consume and generate data in complex ways which may not be obvious to management. This loads risks for global data management projects. This paper investigates an approach combining process mining and knowledge engineering to help manage complex data assets in an international software development process. The research engaged a data management team and other stakeholders over a critical one year period during which the company was involved in an acquisition of another similar sized company. This added significantly to the overall complexity of the enterprise context and decision process. Serious challenges existed with systemic complexity, including the silo-ed nature of IT assets which were not readily amenable to modelling dynamic networks of processes. Preliminary results presented here showed that some features of the combined process mining/ontology development framework would address process management complexity, aiding control of that complex data environment.

Original languageEnglish
Pages (from-to)762-767
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number30
DOIs
Publication statusPublished - 2018

Keywords

  • business process analysis
  • complex systems
  • Enterprise integration
  • Enterprise network design
  • Enterprise Systems
  • implementation
  • Systems interoperability

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