METEORO: Uma abordagem geo-ontológica para suporte à tomada de decisão no domínio de dados de Previsão Numérica do Tempo

Abstract

Weather forecasting is an important application of Science to plan daily activities, being used in agriculture, air traffic, sea, severe weather events alerts, military operations and enterprise systems. The weather forecast information is provided by several systems with different formats, parameters and with a large number of heterogeneous concepts used in different organizations. In view of these facts, the National Meteorological Services have sought to gather information from Numerical Weather Prediction in a single environment to analyze and compare them with the aim of offering support to decision making that leads to a reduction in the number of these heterogeneous concepts. However, these conceptual ambiguities inherent to this domain and the different forms of categorization make the task of gathering this information quite complex. Although there are some ontological approaches in the Weather Forecast data domain, they emphasize the representation of part of the domain, that is, they do not aim at an open and generic approach to interoperability. There are reference models developed with the use of domain ontology based on Unified Foundational Ontology to benefit several domains in terms of reducing conceptual ambiguities. Other approaches benefit from the semantic expressiveness of ontology to assist in the development of a decision support system. Aiming to obtain all these benefits in the domain of Numerical Weather Prediction data, this work proposes the METEORO geospatial ontological approach to support decision making and increase semantic expressiveness, as a solution to promote the semantic enrichment of data from meteorological observations , aiming to reduce conceptual ambiguities of these data.