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Ontologies Based Databases And Information Systems


Ontologies Based Databases And Information Systems

This paper describes a method for using Semantic Web technologies for sharing knowledge in healthcare. It combines deductive databases and ontologies, so that it is possible to extract knowledge that has not been explicitly declared within the database. A representation of the UMLS (Unified Medical Language System) Semantic Network and Metathesaurus was created using the RDF standard, in order to represent the basic medical ontology. The inference over the knowledge base is done by the TRI-DEDALO System, a deductive data-base created to query and update RDF based knowledge sources as well as conventional relational databases. Finally, an ontology was created for the Brazilian National Health Card data interchange format, a standard to capture and transmit health encounter information throughout the country. This paper demonstrates how this approach can be used to integrate heterogeneous information and to answer complex queries in a real world environment.

Abstract:Computational ontologies are machine-processable structures which represent particular domains of interest. They integrate knowledge which can be used by humans or machines for decision making and problem solving. The main aim of this systematic review is to investigate the role of formal ontologies in information systems development, i.e., how these graphs-based structures can be beneficial during the analysis and design of the information systems. Specific online databases were used to identify studies focused on the interconnections between ontologies and systems engineering. One-hundred eighty-seven studies were found during the first phase of the investigation. Twenty-seven studies were examined after the elimination of duplicate and irrelevant documents. Mind mapping was substantially helpful in organising the basic ideas and in identifying five thematic groups that show the main roles of formal ontologies in information systems development. Formal ontologies are mainly used in the interoperability of information systems, human resource management, domain knowledge representation, the involvement of semantics in unified modelling language (UML)-based modelling, and the management of programming code and documentation. We explain the main ideas in the reviewed studies and suggest possible extensions to this research.Keywords: formal ontology; information system; conceptualisation; software development; software design; semantic web; UML; OWL

There is a growing need to define a semantic mapping from a database schema to an ontology. Such a mapping is an integral part of the data integration systems that use an ontology as a unified global view. However, both ontologies and database schemas evolve over time in order to accommodate updated information needs. Once the ontology and the database schema associated with a semantic mapping evolved, it is necessary and important to maintain the validity of the semantic mapping to reflect the new semantics in the ontology and the schema. In this paper, we propose a formulation of the mapping maintenance problem and outline a possible solution using illustrative examples. The main points of this paper are: (1) to differentiate the semantic mapping maintenance problem from the schema mapping adaptation problem which only adapts mappings when schemas change; (2) to develop an approach for specifying the validity of a semantic mapping in terms of two-way legal instances translation between two models; (3) to explore the approach of using simple correspondences to capture changes to ontologies/schemas; and (4) to sketch a solution using examples.

Clinical decision support systems (CDSS) have been shown to reduce medication errors. However, they are underused because of different challenges. One approach to improve CDSS is to use ontologies instead of relational databases. The primary aim was to design and develop OntoPharma, an ontology based CDSS to reduce medication


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