TY - GEN
T1 - Bridging Signals and Human Intelligence - Log Mining-Driven and Meta Model-Guided Ontology Population in Large-Scale IoT
AU - Graf, David
AU - Retschitzegger, Werner
AU - Schwinger, Wieland
AU - Kapsammer, Elisabeth
AU - Baumgartner, Norbert
PY - 2022/8
Y1 - 2022/8
N2 - Large-scale Internet-of-Things (IoT) environments such as Intelligent Transportation Systems are facing tremendous challenges wrt. monitoring their operational technology (OT) not least due to its inherent heterogeneous and evolutionary nature. This situation is often aggravated by the lack of machine-interpretable information about the interdependencies between OT objects in terms of “semantic relationships”, thus considerably impeding the detection of root causes of cross-system errors or interrelated impacts. Therefore, we propose a novel hybrid approach for identifying semantic relationships based on both, mined functional correlations between OT objects based on log files and domain knowledge in terms of an IoT meta model. For this, we firstly contribute a systematic discussion of associated challenges faced in large-scale IoT environments, secondly, we put forward an IoT meta model based on both, industry standards and academic proposals, and finally, we employ this meta model as guidance and target template for the automatic population of semantic relationships into an OT ontology.
AB - Large-scale Internet-of-Things (IoT) environments such as Intelligent Transportation Systems are facing tremendous challenges wrt. monitoring their operational technology (OT) not least due to its inherent heterogeneous and evolutionary nature. This situation is often aggravated by the lack of machine-interpretable information about the interdependencies between OT objects in terms of “semantic relationships”, thus considerably impeding the detection of root causes of cross-system errors or interrelated impacts. Therefore, we propose a novel hybrid approach for identifying semantic relationships based on both, mined functional correlations between OT objects based on log files and domain knowledge in terms of an IoT meta model. For this, we firstly contribute a systematic discussion of associated challenges faced in large-scale IoT environments, secondly, we put forward an IoT meta model based on both, industry standards and academic proposals, and finally, we employ this meta model as guidance and target template for the automatic population of semantic relationships into an OT ontology.
UR - https://www.scopus.com/pages/publications/85135005535
U2 - 10.1007/978-3-031-10986-7_46
DO - 10.1007/978-3-031-10986-7_46
M3 - Conference proceedings
SN - 9783031109850
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 571
EP - 585
BT - Proceeding of the 15th International Conference on Knowledge Science, Engineering and Management (KSEM), Singapore, August 6–8, 2022
A2 - Memmi, Gerard
A2 - Yang, Baijian
A2 - Kong, Linghe
A2 - Zhang, Tianwei
A2 - Qiu, Meikang
ER -
