Mauro Lopes

The Role of Foundational Ontologies for Domain Ontology Engineering: An Industrial Case Study in the Domain of Oil and Gas Exploration and Production

Ontologies are commonly used in computer science either as a reference model to support semantic interoperability, or as an artifact that should be efficiently represented to support tractable automated reasoning. This duality poses a tradeoff between expressivity and computational tractability that should be addressed in different phases of an ontology engineering process. The inadequate choice of a modeling language, disregarding the goal of each ontology engineering phase, can lead to serious problems in the deployment of the resulting model. This article discusses these issues by making use of an industrial case study in the domain of Oil and Gas. The authors make the differences between two different representations in this domain explicit, and highlight a number of concepts and ideas that were implicit in an original OWL-DL model and that became explicit by applying the methodological directives underlying an ontologically well-founded modeling language.

On the Importance of Truly Ontological Distinctions for Ontology Representation Languages: An Industrial Case Study in the Domain of Oil and Gas

Ontologies are commonly used in computer science either as a reference model to support semantic interoperability, or as an artifact that should be efficiently represented to support tractable automated reasoning. This duality poses a tradeoff between expressivity and computational tractability that should be addressed in different phases of an ontology engineering process. The inadequate choice of a modeling language, disregarding the goal of each ontology engineering phase, can lead to serious problems in the deployment of the resulting model. This article discusses these issues by making use of an industrial case study in the domain of Oil and Gas. We make explicit the differences between two different representations in this domain, and highlight a number of concepts and ideas that were implicit in an original OWL-DL model and that became explicit by applying the methodological directives underlying an ontologically well-founded modeling language.

People in Network, Collaboration for Action: New Supporting Requirements

In large-scale collaboration domains, social networks can be a suitable model for allowing people to collaborate in performing collective actions, not only for producing work but also to achieve common and broader objectives. In a previous work, an environment was proposed aiming at supporting specific collaboration requirements for social networks. In this work, these requirements were explored further, searching for an environment that could both improve the initial proposal and to improve social network support in a research project context - RCC-Sw, which aims at defining a social network for software engineering professionals.

Expressing action assertions in foundational-based domain ontologies

Despite all the research efforts in the last decades, information integration is a problem yet to be solved in real organizations, especially when it involves semantic issues. A complete and precise shared representation of all the concepts involved in the integration tasks is required to prevent several kinds of problems, such as misinterpretation of a piece of information by different business stakeholders, inconsistent data integration procedures, and incorrect information exchange between applications. A key goal of any conceptual data model is to provide the best possible understanding of its subjacent domain. Ontologically well-founded conceptual models present themselves as a solution to represent a domain in a more correct and complete scheme. Current well-founded conceptual modeling representation languages, however, focus on the structural perspective. On the other side, there are several restrictions that influence the behavior of the concepts of the domain; these restrictions are frequently represented as business rules. Business rules contribute to restrict the semantics of the domain concepts and their relationships. However, structural and behavioral perspectives are usually represented in distinct and non-integrated artifacts. This separation prevents complete understanding of the underlying semantics of the domain. This work proposes preliminary ideas towards integrating these two domain perspectives in a semantically rich and complete conceptual data model, represented as an ontology. The result is a more complete conceptual model, which may be further used in more reliable information integration processes.

ENTERPRISE ONTOLOGY MANAGEMENT - An Approach based on Information Architecture

Ontologies have gained popularity, but its promises of being a key point to the solution of real-world problems and mitigating interoperability problems at a large scale have not yet been accomplished. Ontology management is at the kernel of this evolution, and there is a lack of adequate strategies and mechanisms for handling it in such a way to contribute to a better alignment between business and IT. This work proposes an approach for enterprise ontology management as part of an Information Architecture initiative. This approach provides a more complete foundation of the ontology lifecycle while guiding the enterprise in this management, by defining a set of processes, roles and competencies required for ontology management. It was applied to a big enterprise in Brazil at the Data Integration department.

REVERSE ENGINEERING A DOMAIN ONTOLOGY TO UNCOVER FUNDAMENTAL ONTOLOGICAL DISTINCTIONS - An Industrial Case Study in the Domain of Oil and Gas Production and Exploration

Ontologies are commonly used in computer science either as a reference model to support semantic interoperability in several scenarios, or as a computer-tractable artifact that should be efficiently represented to be processed. This duality poses a tradeoff between expressivity and computational tractability that should be taken care of in different phases of ontology engineering. In this scenario, the choice of the ontology representation language is crucial, since different languages contain different expressivity and ontological commitments, reflecting on the specific set of available constructs. The inadequate use of a representation language, disregarding the goal of each ontology engineering phase, can lead to serious problems to database design and integration, to domain and systems requirements analysis within the software development processes, to knowledge representation and automated reasoning, and so on. This article presents an illustration of these issues by using a real industrial case study in the domain of Oil and Gas Exploration and Production. We explicit the differences between two different representations of this domain, and highlight a number of concepts and ideas (tacit domain knowledge) that were implicit in the original model represented using an ontology-codification language and that became explicit by applying methodological directives underlying an ontologically well-founded modeling language.