In the last few years, ontologies have been successfully exploited by Decision Support Systems (DSSs) to support some phases of the decisionmaking process. In this paper, we propose to employ an ontological representation for all the content both processed and produced by a DSS in answering requests. This semantic representation supports the DSS in the whole decisionmaking process, and it is capable of encoding (i) the request, (ii) the data relevant for it, and (iii) the conclusions/suggestions/decisions produced by the DSS. The advantages of using an ontology-based representation of the main data structure of a DSS are many: (i) it enables the integration of heterogeneous sources of data available in the web, and to be processed by the DSS, (ii) it allows to track, and to expose in a structured form to additional services (e.g., explanation or case reuse services), all the content processed and produced by the DSS for each request, and (iii) it enables to exploit logical reasoning for some of the inference steps of the DSS decision-making process. The proposed approach have been successfully implemented and exploited in a DSS for personalized environmental information, developed in the context of the PESCaDO EU project.

An Ontological Framework for Decision Support

M. Rospocher;
2012

Abstract

In the last few years, ontologies have been successfully exploited by Decision Support Systems (DSSs) to support some phases of the decisionmaking process. In this paper, we propose to employ an ontological representation for all the content both processed and produced by a DSS in answering requests. This semantic representation supports the DSS in the whole decisionmaking process, and it is capable of encoding (i) the request, (ii) the data relevant for it, and (iii) the conclusions/suggestions/decisions produced by the DSS. The advantages of using an ontology-based representation of the main data structure of a DSS are many: (i) it enables the integration of heterogeneous sources of data available in the web, and to be processed by the DSS, (ii) it allows to track, and to expose in a structured form to additional services (e.g., explanation or case reuse services), all the content processed and produced by the DSS for each request, and (iii) it enables to exploit logical reasoning for some of the inference steps of the DSS decision-making process. The proposed approach have been successfully implemented and exploited in a DSS for personalized environmental information, developed in the context of the PESCaDO EU project.
978-3-642-37995-6
decision support, semantic web, ontology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/990186
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