Ontologies, Disorders and Prototypes

As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field (such as, in the first place, the Web Ontology Language - OWL) do not allow for the representation of concepts in terms of typical traits. The need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific disorders. We favour a hybrid approach to concept representation, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual space. As a preliminary step to apply our proposal to mental disorder concepts, we started to develop an OWL ontology of the schizophrenia spectrum, which is as close as possible to the DSM-5 descriptions

Temporal Representation and Reasoning in OWL 2

The representation of temporal information has been in the center of intensive research activities over the years in the areas of knowledge representation, databases and more recently, the Semantic Web. The proposed approach extends the existing framework of representing temporal information in ontologies by allowing for representation of concepts evolving in time (referred to as “dynamic” information) and of their properties in terms of qualitative descriptions in addition to quantitative ones (i.e., dates, time instants and intervals). For this purpose, we advocate the use of natural language expressions, such as “before” or “after”, for temporal entities whose exact durations or starting and ending points in time are unknown. Reasoning over all types of temporal information (such as the above) is also an important research problem. The current work addresses all these issues as follows: The representation of dynamic concepts is achieved using the “4D-fluents” or, alternatively, the “N-ary relations” mechanism. Both mechanisms are thoroughly explored and are expanded for representing qualitative and quantitative temporal information in OWL. In turn, temporal information is expressed using either intervals or time instants. Qualitative temporal information representation in particular, is realized using sets of SWRL rules and OWL axioms leading to a sound, complete and tractable reasoning procedure based on path consistency applied on the existing relation sets. Building upon existing Semantic Web standards (OWL), tools and member submissions (SWRL), as well as integrating temporal reasoning support into the proposed representation, are important design features of our approach

DTD2OWL2: A New Approach for the Transformation of the DTD to OWL

AbstractThe expansion of data sources existed in the web affects on the quality of research information. The correct answer (answer specific) of a request is all depend terms selected for their construction. Such as these terms sometimes mean more sense, the intended meaning may not be found. Fort this need, the Semantic Web has come to cover the semantic level, it proposed an ontological representation of data sources. This representation is implemented by OWL (Web Ontology Language). The current challenge of the Semantic Web is the transformation of data formats exist (SQL, XML ...) to the form of ontology (RDF, OWL ...), in order to facilitate the integration of data sources exist in the semantic web. Our target is to provide a series of extension concepts of DTD2OWL method, a simple and effective method for transforming XML documents into OWL ontologies

Tool-supported building of DSLs from OWL ontologies

Domain-specific languages (DSLs) are computer languages intended for problem solving in a specific domain. Ontology is a formal representation of a set of concepts from a particular domain and the relations between them. An ontology may be used to describe a domain and to reason about the entities within the domain. This paper presents an Ontology2DSL framework to build DSLs from OWL ontologies. Ontology2DSL enables the semi-automated construction of a formal grammar and programs from an OWL ontology. The design approach, the functionalities of the framework, and a case study are also addressed in this paper. Special attention is paid to the architecture that encompasses the following components: the transformation pattern builder, the OWL parser, the rule reader, the rule execution component and the transaction logger

Hermes: an Ontology-Based News Personalization Portal

Nowadays, news feeds provide Web users with access to an unlimited amount of news items, however only a subset of them is relevant. Therefore, users should be able to select the most relevant concepts, about which they want to retrieve news. Although keyword search engines provide users with the ability to filter news items, they lack the power of understanding the domain where the news items reside. The aim of this paper is to propose a solution that provides users with the ability to ask for news items related to specific concepts they are interested in. This is accomplished by creating an ontology, developing a classifying system that populates the ontology by making use of a knowledge base, and providing an innovative graph representation of the ontology to retrieve relevant news items. A characteristic feature of our approach is the consideration of both concepts and concept relationships for the retrieval of user-relevant items.semantic web; news classification; ontologies; OWL; SPARQL; decision support

Using Semantic Web Technology to Automate Data Integration in Grid and Web Service Architectures

While the Grid and Web Services have helped us support heterogeneous resource access through the use of service oriented architectures, they have not addressed the issue of heterogeneous data representation. Since service providers often describe their service interfaces using different data models than those assumed by the client, it is common for additional processing to be required to compensate for the mismatch in data formats. By utilising technology from the Semantic Web, we are able to augment existing Web Service systems with middleware to automatically perform data harmonisation when a syntactic mismatch occurs. To achieve this, we have developed a mapping language which can be used to annotate XML data structures with OWL concepts and properties, a Mapping Language Engine to implement this language, and a Dynamic Web Service Invocation component to execute Web Services

Automatic Transformation of Relational Database Schema into OWL Ontologies

Ontology alignment, or ontology matching, is a technique to map different concepts between ontologies. For this purpose at least two ontologies are required. In certain scenarios, such as data integration, heterogeneous database integration and data model compatibility evaluation, a need to transform a relational database schema to an ontology can arise. To conduct a successful transformation it is necessary to identify the differences between relational database schema and ontology information representation methods, and then to define transformation rules. The most straight forward but time consuming way to carry out transformation is to do it manually. Often this is not an option due to the size of data to be transformed. For this reason there is a need for an automated solution.The automatic transformation of OWL ontology from relational database schema is presented in this paper; the data representation differences between relational database schema and OWL ontologies are described; the transformation rules are defined and the transformation tool’s prototype is developed to perform the described transformation

An Efficient Bit Vector Approach to Semantics-Based Machine Perception in Resource-Constrained Devices

The primary challenge of machine perception is to define efficient computational methods to derive high-level knowledge from low-level sensor observation data. Emerging solutions are using ontologies for expressive representation of concepts in the domain of sensing and perception, which enable advanced integration and interpretation of heterogeneous sensor data. The computational complexity of OWL, however, seriously limits its applicability and use within resource-constrained environments, such as mobile devices. To overcome this issue, we employ OWL to formally define the inference tasks needed for machine perception – explanation and discrimination – and then provide efficient algorithms for these tasks, using bit-vector encodings and operations. The applicability of our approach to machine perception is evaluated on a smart-phone mobile device, demonstrating dramatic improvements in both efficiency and scale

Malaysia indigenous herbs knowledge representation

The values of Malaysia indigenous herbs are not limited to its medicinal benefits but also in local and traditional knowledge of each herb.However, this knowledge is scattered and unorganized in internet and merely own by local people that led to difficulty in designing knowledge based system.This paper proposed a Malaysia indigenous herbs knowledge representation and its implementation in Web Ontology Language (OWL) using Protégé 4.2. The herbs knowledge mainly in preparation methods and plants part uses is collected from literatures and experts in herbal field.Additional interview session is conducted with expert to validate the information gathered.In order to ensure the knowledge model and ontology view is well defined, a prototype of knowledge based system is developed based on the ontology classes or concepts and relationships defined which requires conversion the OWL ontology into the relational database system at first hand