Semantic Model Based Approach for Knowledge Intensive Processes

Many business processes present in modern enterprises are loosely defined, highly interactive, involve frequent human interventions. They are coupled with a multitude of abstract entities defined within an enterprise architecture. Further, they demand agility and responsiveness to address the frequently changing business requirements. Traditional process modelling and knowledge management technologies are not adequate to represent and support those processes. In this paper, we discuss how a process management system based on semantic models can be used to address the needs of non-traditional and knowledge intensive processes. The modelling capabilities of the framework are demonstrated via a case study and evaluated using set requirements that KIP supporting process management system should have. Finally, we discuss how this semantic model based solution can be improved further to cater for the management and execution of knowledge-intensive business processes in a broader context.

[1]  Massimo Mecella,et al.  SmartPM: An Adaptive Process Management System through Situation Calculus, IndiGolog, and Classical Planning , 2014, KR.

[2]  Martin Hepp,et al.  An Ontology Framework for Semantic Business Process Management , 2007, Wirtschaftsinformatik.

[3]  Youcef Baghdadi,et al.  Modelling business process with services: towards agile enterprises , 2014, Int. J. Bus. Inf. Syst..

[4]  Onur Demirörs,et al.  PROMPTUM Toolset: Tool Support for Integrated Ontologies and Process Models , 2016, Business Process Management Workshops.

[5]  Claudio Di Ciccio,et al.  Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches , 2015, Journal on Data Semantics.

[6]  Santhosh Kumaran,et al.  On the Duality of Information-Centric and Activity-Centric Models of Business Processes , 2008, CAiSE.

[7]  Richard Hull,et al.  Business Artifacts: A Data-centric Approach to Modeling Business Operations and Processes , 2009, IEEE Data Eng. Bull..

[8]  Jan Mendling,et al.  Towards a Methodology for Semantic Business Process Modeling and Configuration , 2009, ICSOC Workshops.

[9]  Corine Cauvet,et al.  Business Process Modeling: A Service-Oriented Approach , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[10]  Fethi A. Rabhi,et al.  From Requirements to Data Analytics Process: An Ontology-Based Approach , 2018, Business Process Management Workshops.

[11]  Madhushi Bandara,et al.  Big Data Analytics Has Little to Do with Analytics , 2017, ASSRI.

[12]  Richard Hull,et al.  Declarative business artifact centric modeling of decision and knowledge intensive business processes , 2011, 2011 IEEE 15th International Enterprise Distributed Object Computing Conference.

[13]  Onur Demirörs,et al.  A Digital Interaction Framework for Managing Knowledge Intensive Business Processes , 2018, ASSRI.

[14]  Norbert Gronau,et al.  Management of Knowledge Intensive Business Processes , 2004, Business Process Management.

[15]  Lila Rao-Graham,et al.  Building ontology based knowledge maps to assist business process re-engineering , 2012, Decis. Support Syst..

[16]  O. Demirors,et al.  Process modeling methodologies for improvement and automation , 2011, 2011 IEEE International Conference on Quality and Reliability.