Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language

João Luiz Moreira; Luis  Ferreira Pires; Marten J. van Sinderen; P. Dockhorn Costa

doi:10.5220/0006208904670477

Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language

João Luiz Moreira, Luis Ferreira Pires, Marten J. van Sinderen, P. Dockhorn Costa

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

11 Citations (Scopus)

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 applica tions, being suitable for other application scenarios.

Original language	English
Title of host publication	MODELSWARD 2017
Subtitle of host publication	proceedings of the 5th intrnational conference on Model-Driven Engineering and Software Development: Porto, Portugal, February 19-21, 2017
Editors	Luis Ferreira Pires, Slimane Hammoudi, Bran Selic
Place of Publication	Sétubal
Publisher	SCITEPRESS
Pages	467-477
Number of pages	11
ISBN (Print)	978-989-758-210-3
DOIs	https://doi.org/10.5220/0006208904670477
Publication status	Published - 27 Feb 2017
Event	5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017 - Porto, Portugal Duration: 19 Feb 2017 → 21 Feb 2017 Conference number: 5

Conference

Conference	5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017
Abbreviated title	MODELSWARD 2017
Country/Territory	Portugal
City	Porto
Period	19/02/17 → 21/02/17

Keywords

Early Warning System
Public Health Surveillance
Situation Modelling Language
Events Processing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.5220/0006208904670477

http://scitepress.org/PublicationsDetail.aspx?ID=HyFm0ZsEZY8=&t=1

Cite this

Moreira, J. L., Ferreira Pires, L., van Sinderen, M. J., & Dockhorn Costa, P. (2017). Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language. In L. F. Pires, S. Hammoudi, & B. Selic (Eds.), MODELSWARD 2017: proceedings of the 5th intrnational conference on Model-Driven Engineering and Software Development: Porto, Portugal, February 19-21, 2017 (pp. 467-477). SCITEPRESS. https://doi.org/10.5220/0006208904670477

Moreira, João Luiz ; Ferreira Pires, Luis ; van Sinderen, Marten J. et al. / Ontology-Driven Conceptual Modeling for Early Warning Systems : Redesigning the Situation Modeling Language. MODELSWARD 2017: proceedings of the 5th intrnational conference on Model-Driven Engineering and Software Development: Porto, Portugal, February 19-21, 2017. editor / Luis Ferreira Pires ; Slimane Hammoudi ; Bran Selic. Sétubal : SCITEPRESS, 2017. pp. 467-477

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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 applica tions, being suitable for other application scenarios.",

keywords = "Early Warning System, Public Health Surveillance, Situation Modelling Language, Events Processing",

author = "Moreira, {Jo{\~a}o Luiz} and {Ferreira Pires}, Luis and {van Sinderen}, {Marten J.} and {Dockhorn Costa}, P.",

year = "2017",

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editor = "Pires, {Luis Ferreira} and Slimane Hammoudi and Bran Selic",

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Moreira, JL , Ferreira Pires, L , van Sinderen, MJ & Dockhorn Costa, P 2017, Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language. in LF Pires, S Hammoudi & B Selic (eds), MODELSWARD 2017: proceedings of the 5th intrnational conference on Model-Driven Engineering and Software Development: Porto, Portugal, February 19-21, 2017. SCITEPRESS, Sétubal, pp. 467-477, 5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017, Porto, Portugal, 19/02/17. https://doi.org/10.5220/0006208904670477

Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language. / Moreira, João Luiz ; Ferreira Pires, Luis ; van Sinderen, Marten J. et al.
MODELSWARD 2017: proceedings of the 5th intrnational conference on Model-Driven Engineering and Software Development: Porto, Portugal, February 19-21, 2017. ed. / Luis Ferreira Pires; Slimane Hammoudi; Bran Selic. Sétubal: SCITEPRESS, 2017. p. 467-477.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Ontology-Driven Conceptual Modeling for Early Warning Systems

T2 - 5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017

AU - Moreira, João Luiz

AU - Ferreira Pires, Luis

AU - van Sinderen, Marten J.

AU - Dockhorn Costa, P.

N1 - Conference code: 5

PY - 2017/2/27

Y1 - 2017/2/27

N2 - 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 applica tions, being suitable for other application scenarios.

AB - 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 applica tions, being suitable for other application scenarios.

KW - Early Warning System

KW - Public Health Surveillance

KW - Situation Modelling Language

KW - Events Processing

U2 - 10.5220/0006208904670477

DO - 10.5220/0006208904670477

M3 - Conference contribution

SN - 978-989-758-210-3

SP - 467

EP - 477

BT - MODELSWARD 2017

A2 - Pires, Luis Ferreira

A2 - Hammoudi, Slimane

A2 - Selic, Bran

PB - SCITEPRESS

CY - Sétubal

Y2 - 19 February 2017 through 21 February 2017

ER -

Moreira JL , Ferreira Pires L , van Sinderen MJ, Dockhorn Costa P. Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language. In Pires LF, Hammoudi S, Selic B, editors, MODELSWARD 2017: proceedings of the 5th intrnational conference on Model-Driven Engineering and Software Development: Porto, Portugal, February 19-21, 2017. Sétubal: SCITEPRESS. 2017. p. 467-477 doi: 10.5220/0006208904670477

Ontology-Driven Conceptual Modeling for Early Warning Systems: Redesigning the Situation Modeling Language

Abstract

Conference

Keywords

UN SDGs

Access to Document

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Cite this