Enterprise Level Integration of Ontology Engineering and Process Mining for Management of Complex Data and Processes to improve Decision System. Issue 30 (2018)

• Record Type: Journal Article
• Authors: Thakar, Tejan; Tsultrim, Tenzin; Stapleton, Larry; Doyle, Liam
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 30(2018)
• Page Start: 762
• Page End: 767
• Publication Date: 2018
• Subjects: Enterprise integration -- Systems interoperability -- Enterprise network design -- implementation -- Enterprise Systems -- business process analysis -- complex systems; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.11.200
• Languages: English
• ISSNs: 2405-8963

Abstract

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.