Abstract
Today, situation management in maritime areas assumes acquisition, integration, and processing of huge amounts of information from various sources such as geographical information system (GIS) data, current and forecasted weather conditions, current and planned/forecasted positions, and movements of ships in the considered area. This has caused the appearance of a new aggregated term of “Digital Ocean” integrating various technologies. This paper proposes an approach to sea rescue operation management based on the service-oriented architecture (SOA) and digital ocean technologies. The approach assumes representation of the operation members and information sources with Web services. This makes it possible to replace maritime situation modeling with modeling of a Web service network. The major idea of the approach is described together with its architecture and major components. Application of the approach is demonstrated on the case study of hurricane/storm situation management.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Albani A, Dietz J (2006) The Benefit of Enterprise Ontology in Identifying Business Components. In: The Past and Future of Information Systems: 1976-2006 and Beyond. In: Proceedings of IFIP 19th World Computer Congress, TC-8, Information System Stream (WCC2006), pp 243–254.
Atkinson C, C, Groß H-G, Kühne T (2002) Towards a General Component Model for Web-Based Applications. In: Annals of Software Engineering, 13(1-4):35–69
Balmelli L, Brown D, Cantor M, Mott M. (2006) Model-Driven Systems Development. In: IBM Systems Journal, IBM, 45(3): 569–585
CADRC (2009) KML Sandbox: An Facility Based on SOA Principles. CADRD Currents, Fall, 2009, Collaborative Agent Design Research Center (CADRC), California Polytechnic State University, San Luis Obisro.
Dey A.K. (2001) Understanding and Using Context. Personal and Ubiquitous Computing J, 5(1):4–7
Grüninger M (1996) Ontologies: Principles, methods and applications. Knowledge Engineering Review, 11(2):93–155
Langlois B, D (2004) MDSOFA: A Model-Driven Software Factory. In: Position papers for OOPSLA & GPCE Workshop “Best Practices for Model Driven Software Development”, http://www.softmetaware.com/oopsla2004/langlois.pdf/, last accessed Sep. 20, 2010.
Liu X, Zhang X, Chi T, Qu H, Jiang Y (2009) Study on China Digital Ocean Prototype System. In: proceedings of the WRI World Congress on Software Engineering (WCSE’09), IEEE, pp 466 – 469
Seidman DI, Ritsko JJ (2006) Preface. In: IBM Systems Journal, IBM, 45(3):449-450
Smirnov A, Levashova T, Shilov N (2009) Context-Based Intelligent Service for Healthcare Applications. In: Dwivedi A (ed.) Handbook of Research on Information Technology Management and Clinical Data Administration in Healthcare, Medical Information Science Reference, 1:128–142
Smirnov A, Kashevnik A, Levashova T, Shilov N (2007) Context-Driven Information Fusion for Operational Decision Making in Humanitarian Logistics. In: Popovich V, Korolenko K, Schrenk M (eds.): Lecture Notes in Geoinformation and Cartography. Proceedings of the third International Workshop on Information Fusion and Geographic Information Systems (IFGIS 2007), Springer, pp 69–83
Smirnov A, M, Chilov N, Levashova T (2005) Constraint-driven methodology for context-based decision support. Design, Building and Evaluation of Intelligent DMSS (Journal of Decision Systems), Lavoisier, 14(3):279–301
Smirnov A, Shilov N, Levashova T, Kashevnik A (2009) GIS for profile-based context formation in situation management. In: Information Fusion and Geographic Information Systems, Proceedings of the Fourth International Workshop, IFGIS 2009 (electronic proceedings).
Stahl T, Voelter M (2006) Model-Driven Software Development: Technology, Engineering, Management. Wiley, 444p
The Digital Ocean Theme Team, http://web.mit.edu/seagrant/digitalocean/, last accessed Nov. 19, 2010.
Acknowledgments
Some of the results are due to research carried out as a part of the project funded by grants # 09-07-00436, # 11-07-00045, # 09-07-00066, and 10-08-90027 of the Russian Foundation for Basic Research, and project # 213 of the research program “Intelligent Information Technologies, Mathematical Modelling, System Analysis and Automation” of the Russian Academy of Sciences.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Smirnov, A., Kashevnik, A., Shilov, N. (2011). SOA-Based Modeling for Digital Ocean: Approach and Architecture. In: Popovich, V., Claramunt, C., Devogele, T., Schrenk, M., Korolenko, K. (eds) Information Fusion and Geographic Information Systems. Lecture Notes in Geoinformation and Cartography(), vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19766-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-19766-6_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19765-9
Online ISBN: 978-3-642-19766-6
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)