Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language
João L. R. Moreira, Luís Ferreira Pires, Marten van Sinderen, Patricia Dockhorn Costa
2017
Abstract
An early warning system (EWS) is an integrated system that supports the detection, monitoring and alerting of emergency situations. A possible application of an EWS is in epidemiological surveillance, to detect infectious disease outbreaks in geographical areas. In this scenario, a challenge in the development and integration of applications on top of EWS is to achieve common understanding between epidemiologists and software developers, allowing the specification of rules resulted from epidemiological studies. To address this challenge this paper describes an ontology-based model-driven engineering (MDE) framework that relies on the Situation Modelling Language (SML), a knowledge specification technique for situation identification. Some requirements are realized by revisiting SML, which resulted in a complete redesign of its semantics, abstract and concrete syntaxes. The initial validation shows that our framework can accelerate the generation of high quality situation-aware applications, being suitable for other application scenarios.
DownloadPaper Citation
in Harvard Style
L. R. Moreira J., Ferreira Pires L., van Sinderen M. and Dockhorn Costa P. (2017). Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language . In Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD, ISBN 978-989-758-210-3, pages 467-477. DOI: 10.5220/0006208904670477
in Bibtex Style
@conference{modelsward17,
author={João L. R. Moreira and Luís Ferreira Pires and Marten van Sinderen and Patricia Dockhorn Costa},
title={Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language},
booktitle={Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,},
year={2017},
pages={467-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006208904670477},
isbn={978-989-758-210-3},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,
TI - Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language
SN - 978-989-758-210-3
AU - L. R. Moreira J.
AU - Ferreira Pires L.
AU - van Sinderen M.
AU - Dockhorn Costa P.
PY - 2017
SP - 467
EP - 477
DO - 10.5220/0006208904670477