Fri, 12 June, 2020
Why WeldGalaxy ontologies for data modelling?
Knowledge management, marketplaces, the information management systems and structured query formulation languages are important means of retrieving information. Writing structured queries is a powerful method to access data since it allows end-users to formulate complex database queries by learning specialised query languages. Currently, information retrieval has turned out to be more complicated when linking with data mining, decision support systems or tools and analytics applications.
The ontologies express relationships help us to link multiple concepts to other concepts in a variety of ways. Thus, in the context of information retrieval in WeldGalaxy, the ontology or semantic-based approach supports the domain conceptual context (i.e. providing a framework for welding concepts and materials) which has been adapted for data modelling and information retrieval. Ontology-based information retrieval mainly aims at improving the interface between data and search requests in order to bring the result sets closer to the users’ research requirements and improve results when retrieving information.
The WeldGalaxy project develops a welding and marketplace oriented ontology to support a shared data model, agreed and detailed model (or set of concepts) for decision making and solving problems in the welding domain; which can be used as a semantic based model of the data, combined with the associated domain knowledge to define links between different types of knowledge. Thus, the WeldGalaxy ontology and data model provides the basis for supporting information searching for knowledge discovery in components, such as the Knowledge Base Engineering (KBE) and Chatbot.
The WeldGalaxy Ontology development is led by the LifeSTech research group of the Universidad Politécnica de Madrid in close collaboration with TWI, the Leicester University, EKON and Technovative Solutions.