@inproceedings{fbe0bd84bfe140afa95a6cd66aff5d59,
title = "Behavior ontology to model collective behavior of emergency medical systems",
abstract = "It is very important to understand system behaviors in collective pattern for each knowledge domain. However, there are structural limitations to represent collective behaviors due to the size of system components and the complexity of their interactions, causing the state explosion problem. Further composition with other systems is mostly impractical due to exponential growth of their size and complexity. This paper presents a practical method to model the collective behaviors, based on a new concept of domain engineering: behavior ontology. Two domains are selected to demonstrate the method: Emergency Medical Service (EMS) and Health Care Service (HCS) systems. The examples show that the method is very effective and efficient to construct a hierarchy of collective behaviors in a lattice and that the composition of two collective behaviors is systematically performed by the composition operation of two lattices. The method can be one of the most innovative approaches in representing system behaviors in collective pattern, as well as in minimization of system states to reduce system complexity. For implementation, a prototype tool, called PRISM, has been developed on ADOxx Meta-Modelling Platform.",
keywords = "ADOxx, Behavior ontology, Collective behavior, PRISM",
author = "Junsup Song and Maryam Rahmani and Moonkun Lee",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 36th International Conference on Conceptual Modeling, ER 2017 held in Conjuction with the 3rd International Workshop on Modeling for Ambient Assistance and Healthy Ageing, AHA 2017, 6th International Workshop on Modeling and Management of Big Data, MoBiD 2017, 4th International Workshop on Conceptual Modeling in Requirements and Business Analysis, MREBA 2017, 5th International Workshop on Ontologies and Conceptual Modeling, OntoCom 2017 and 4th Workshop on Quality of Models and Models of Quality, QMMQ 2017 ; Conference date: 06-11-2017 Through 09-11-2017",
year = "2017",
doi = "10.1007/978-3-319-70625-2\_1",
language = "English",
isbn = "9783319706245",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "5--15",
editor = "\{de Cesare\}, Sergio and Ulrich Frank",
booktitle = "Advances in Conceptual Modeling - ER 2017 Workshops AHA, MoBiD, MREBA, OntoCom, and QMMQ, Proceedings",
}