Integration Of Domain Ontologies Research Articles

Semi-automated integration of domain ontologies to DSL meta-models

This paper investigates the use of ontologies for the development of Domain-Specific Languages (DSL). In Model-based Software Development (MBSD), ontologies as formal models are mostly used in the phase of domain analysis as formal representations of domain models and requirements of a system. In this paper, we extend this view by introducing a concept of a DSL meta-model ontology that is defined as consisting of system ontology of a MSDB tool linked to one or more domain ontologies and external software artefacts. According to the solution presented in this paper, the given domain ontologies are semi-automatically integrated into a DSL meta-model using a set of transformations between constructs of ontology modelling language OWL and a modelling language used for representing DSL meta-models. This approach enables a dynamic semantic composition of a DSL meta-model and is prototypically implemented in Java as an extension to the DSL development tool CoCoViLa.

Semi-automated integration of domain ontologies to DSL meta-models

This paper investigates the use of ontologies for the development of Domain-Specific Languages (DSL). In Model-based Software Development (MBSD), ontologies as formal models are mostly used in the phase of domain analysis as formal representations of domain models and requirements of a system. In this paper, we extend this view by introducing a concept of a DSL meta-model ontology that is defined as consisting of system ontology of a MSDB tool linked to one or more domain ontologies and external software artefacts. According to the solution presented in this paper, the given domain ontologies are semi-automatically integrated into a DSL meta-model using a set of transformations between constructs of ontology modelling language OWL and a modelling language used for representing DSL meta-models. This approach enables a dynamic semantic composition of a DSL meta-model and is prototypically implemented in Java as an extension to the DSL development tool CoCoViLa.

On a Holistic Modeling Approach for Managing Carbon Emission Ecosystems

Effective use of historical volumes of heterogeneous and multidimensional data is a major challenge, especially projects associated with potential applications of carbon emission ecosystems. Data science in these applications becomes tedious when such varied data are accumulated and or distributed in multiple domains. Design, development, and implementation of sustainable geological storages are crucial for managing carbon dioxide (CO2) emissions and its modeling process. The purpose of the research is to address major challenges and how best a robust “ontology-based multidimensional data warehousing and mining” approach can resolve issues associated with carbon ecosystems. The conceptualized relationships deduced among multiple domains, integration of domain ontologies, data mining, visualization, and interpretation artefacts are highlights of the study. Several data, plot, and map views are extracted from metadata storage for interpreting new knowledge on carbon emissions. Statistical mining models describe data attributes’ correlations, patterns, and trends that can help in predicting future forecast of CO2 emissions worldwide.

Ontology-based information integration and sharing for collaborative part and tooling development

One critical factor in collaborative part and tooling development is the information integration and sharing. After analyzing characteristics of the collaboration process, the problem of information integration and sharing is transformed into a problem of domain ontology integration and sharing. First, an activity model is presented to describe interactions among domains of part, process, and tooling. Next, three local ontologies are constructed to serve as formal, explicit specifications of domain-specific information. To integrate local ontologies as global ontology, the relations and constrains among domains are explicitly represented using Semantic Web Rule Language. Then, the ontology sharing method via similarity matching is studied. Finally, the proposed approach is demonstrated by a case.

Uso de ontologías para la mejora de resultados de motores de búsqueda web

With the increasing number of web sites, the time spent by users reviewing the results also increases. In addition, the nature of web content is semantically heterogeneous and oriented to people who will be able to understand it. Frequently the results from search engines do not correspond to the expected topic. One approach to improve the results is to match the content of the web pages with a formal vocabulary on the topic (ontology) and with the informal vocabulary (common terms of the topic but not in the ontology). This paper describes a web search method that takes advantage of ontologies to reduce the search area of certain topics. With this approach the relevance of search engine results is enhanced by filtering the content through the integration of domain ontologies, the WordNet thesaurus, and a hierarchical similarity measure. Thus, the improvement on the relevance of results reduces the time required to review such results.