TY - JOUR A1 - Rietzke, Eric A1 - Maletzki, Carsten A1 - Bergmann, Ralph A1 - Kuhn, Norbert T1 - Execution of knowledge-intensive processes by utilizing ontology-based reasoning T2 - Journal on Data Semantics N2 - Modeling and executing knowledge-intensive processes (KiPs) are challenging with state-of-the-art approaches, and the specific demands of KiPs are the subject of ongoing research. In this context, little attention has been paid to the ontology-driven combination of data-centric and semantic business process modeling, which finds additional motivation by enabling the division of labor between humans and artificial intelligence. Such approaches have characteristics that could allow support for KiPs based on the inferencing capabilities of reasoners. We confirm this as we show that reasoners can infer the executability of tasks based on a currently researched ontology- and data-driven business process model (ODD-BP model). Further support for KiPs by the proposed inference mechanism results from its ability to infer the relevance of tasks, depending on the extent to which their execution would contribute to process progress. Besides these contributions along with the execution perspective (start-to-end direction), we will also show how our approach can help to reach specific process goals by inferring the relevance of process elements regarding their support to achieve such goals (end-to-start direction). The elements with the most valuable process progress can be identified in the intersection of both, the execution and goal perspective. This paper will introduce this new approach and verifies its practicability with an evaluation of a KiP in the field of emergency call centers. KW - Prozessmanagement KW - Unterstützungssystem KW - ontology KW - data-oriented business process KW - knowledge-intensive process KW - inferencing Y1 - 2021 UR - https://hst.opus.hbz-nrw.de/frontdoor/index/index/docId/105 UR - https://nbn-resolving.org/urn:nbn:de:hbz:tr5-1051 VL - 10 IS - 1-2 SP - 3 EP - 18 PB - Springer Nature ER -