DCR-KiPN a hybrid modeling approach for knowledge-intensive processes

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Hybrid modeling approaches have been proposed to represent processes that have both strictly regulated parts and loosely regulated parts. Such process is so-called Knowledge-intensive Process (KiP), which is a sequence of activities based on intense knowledge use and acquisition. Due to these very particular characteristics, the first author previously proposed the Knowledge-intensive Process Ontology (KiPO) and its subjacent notation (KiPN). However, KiPN still fails to represent the declarative perspective of a KiP. Therefore, in this paper, we propose to improve KiPN by integrating it with the declarative process modeling language DCR Graphs. DCR-KiPN is a hybrid process modeling notation that combines a declarative process model language (activities and business rules) with the main aspects of a KiP, such as cognitive elements (decision rationale towards goals, beliefs, desires and intentions), interactions and knowledge-exchange among its participants.

Original languageEnglish
Title of host publicationConceptual Modeling - 38th International Conference, ER 2019, Proceedings
EditorsAlberto H.F. Laender, Barbara Pernici, Ee-Peng Lim, José Palazzo M. de Oliveira
Number of pages9
PublisherSpringer VS
Publication date2019
ISBN (Print)9783030332228
Publication statusPublished - 2019
Event38th International Conference on Conceptual Modeling, ER 2019 - Salvador, Brazil
Duration: 4 Nov 20197 Nov 2019


Conference38th International Conference on Conceptual Modeling, ER 2019
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11788 LNCS

    Research areas

  • Hybrid process notation, Knowledge-intensive Process

ID: 239961804