Building a Schistosomiasis Process Ontology for an Epidemiological Monitoring System
This chapter describes the design of an ontology that aims to support a monitoring system for schistosomiasis. On one hand, a domain ontology for the schistosomiasis is built to support communication and collaborative work between domain experts along the
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Building a Schistosomiasis Process Ontology for an Epidemiological Monitoring System Gaoussou Camara, Sylvie Despres, Rim Djedidi and Moussa Lo
Abstract This chapter describes the design of an ontology that aims to support a monitoring system for schistosomiasis. On one hand, a domain ontology for the schistosomiasis is built to support communication and collaborative work between domain experts along the monitoring steps. The domain ontology also supports data and application integration and allows some reasoning capabilities. On the other hand, a process ontology of the schistosomiasis spreading is built for explanations and decision-making. Furthermore, the possibilities of using this process ontology for prediction are also worth considering. Here, we have focused on the design of the process ontology of infectious disease spreading and its extension to schistosomiasis. We aim to provide a formal theory in the health domain to conceptualize the processes of the infectious disease spreading and to present reasoning capabilities on the disease occurrences within a population. We emphasize on the basic entities and their relations within the complex process of infectious disease spreading. A multi-level analysis of the global dynamics is provided, taking into account biomedical, clinical and epidemiological dependences. We then propose a formalization of the infectious disease spreading process. Finally, we extend the process ontology for schistosomiasis spreading in Senegal.
3.1 Introduction The context of this chapter is the design of an epidemiological monitoring system whose main goals is to prevent and control an epidemiological phenomenon. A monitoring system aims to detect the event occurrences constituting risk factors for G. Camara (&) S. Despres R. Djedidi LIM&BIO, Université Paris, 13, 74 rue Marcel Cachin 93017 Bobigny, France e-mail: [email protected] G. Camara M. Lo LANI, Université Gaston Berger, B.P.234Saint-Louis, Sénégal
C. Faucher and L. C. Jain (eds.), Innovations in Intelligent Machines-4, Studies in Computational Intelligence 514, DOI: 10.1007/978-3-319-01866-9_3, Springer International Publishing Switzerland 2014
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disease spreading. Predictions are then made for evaluating consequences and suggesting action plans to prevent identified risks and act in advance [1]. Infectious disease spreading is considered as a system made of several entities (host, vector, pathogen agent, risk factors, etc.) whose interactions lead to event emergence (new disease cases, water infestation, etc.) at different spatial (regional, continental, etc.) and temporal (seasonal) levels. Infectious disease spreading, considering its evolution and emergence properties, is characterized as complex systems and can therefore be modeled as a process [2]. After presenting the ontology-based architecture of an epidemiological monitoring system, we focus on building an ontology of infectious disease spreading process that is then extended for schistosomiasis. Although Infectious Dis
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