|Resumo: ||Ontology driven conceptual modeling focuses on accurately representing a domain of interest, instead of making information fit an arbitrary set of constructs. It may be used for different purposes, like to achieve semantic interoperability (Nardi, Falbo and Almeida, 2013), development of knowledge representation models (Guizzardi and Zamborlini, 2012) and language evaluation (Santos, Almeida and Guizzardi,2010). Regardless its final application, a model must be accurately defined in order for it to be a successful solution.
This new branch of conceptual modeling improves traditional techniques by taking into consideration ontological properties, such as rigidity, identity and dependence, which are derived from a foundational ontology. This increasing interest in more expressive languages for conceptual modeling is shown by OMGs request for language proposals for the Semantic Information Model Federation (SIMF) (OMG,2011). OntoUML (Guizzardi, 2005) is an example of a language designed for that purpose.Its metamodel (Carraretto, 2010) is designed to comply to the Unified Foundational Ontology (UFO). It focus on structural aspects of individuals and universals.Grounded on human cognition and linguistics, it aims to provide the most basic categories in which humans understand and classify things around them.In (Guizzardi, 2010) Guizzardi quotes the famous Dijkstras lecture, in which he discusses the humble programmer and makes an analogy entitled the humble ontologist. He argues that the task of ontology-driven conceptual modeling is extremely complex and thus, modelers should surround themselves with as many
tools as possible to aid in the development of the ontology. These complexities arise from different sources. A couple of them come from foundational ontology itself, both its modal nature, which imposes modelers to deal with possibilities, and the many different restrictions of each ontological category. But they also come from the need of accurately defining instance level constraints, which require additional rules, outside of the languages graphical notation.
To help modelers to develop high quality OntoUML models, a number of tools have been proposed to aid in different phases of conceptual modeling. From the
construction of the models themselves using design patterns questions (Guizzardi et al., 2011), to automatic syntax verification (Benevides, 2010) and model validation through simulation (Benevides et al., 2010).
The importance of domain specification that accurately captures the intended
conceptualization has been recognized by both the traditional conceptual modeling community (Moody et al., 2003) and the ontology community (Vrandečić, 2009). In this research we want to improve (Benevides et al., 2010) initiative, but focus exclusively on the validation of ontology driven conceptual models, and not on verification. With the complexity of the modeling activity in mind, we want to help modelers to systematically produce high quality ontologies, improving precision and coverage (Gangemi et al., 2005) of the models. We intend to make the simulationbased approach available for users that are not experts in the formal method, relieving them of the need to learn yet another language, solely for the purpose of validating their models.|