Data on observed and forecasted environmental conditions, such as weather, air quality and pollen, are offered in a great variety in the web and serve as basis for decisions taken by a wide range of the population. However, the value of these data is limited because their quality varies largely and because the burden of their interpretation in the light of a specific context and in the light of the specific needs of a user is left to the user herself. To remove this burden from the user, we propose an environmental decision support system (DSS) model with an ontology-based knowledge base as its integrative core. The availability of an ontological knowledge representation allows us to encode in a uniform format all knowledge that is involved (environmental background knowledge, the characteristic features of the profile of the user, the formal description of the user request, measured or forecasted environmental data, etc.) and apply advanced reasoning techniques on it. The result is an advanced DSS that provides high quality environmental information for personalized decision support.

Ontology-centered environmental information delivery for personalized decision support

Rospocher, Marco;Serafini, Luciano
2015

Abstract

Data on observed and forecasted environmental conditions, such as weather, air quality and pollen, are offered in a great variety in the web and serve as basis for decisions taken by a wide range of the population. However, the value of these data is limited because their quality varies largely and because the burden of their interpretation in the light of a specific context and in the light of the specific needs of a user is left to the user herself. To remove this burden from the user, we propose an environmental decision support system (DSS) model with an ontology-based knowledge base as its integrative core. The availability of an ontological knowledge representation allows us to encode in a uniform format all knowledge that is involved (environmental background knowledge, the characteristic features of the profile of the user, the formal description of the user request, measured or forecasted environmental data, etc.) and apply advanced reasoning techniques on it. The result is an advanced DSS that provides high quality environmental information for personalized decision support.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/301858
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